Implementation of the EM Algorithm for Maximum Likelihood Estimation of a Random Effects Model for One Longitudinal Ordinal Outcome

2010 Mathematics Subject Classification: 62J99.

On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can be recorded instead. This is the so-called grouped data. In this paper, we will show the existence and uniqueness of the maximum likelihood estimators of the two parameters of the underlying lognormal distribution with Type-I censored data and grouped data. The proof was first established under the case of normal distribution and extended to the lognormal distribution through invariance property. The results are applied to estimate the median and mean of the lognormal population.

RATE OF CONVERGENCE OF MAXIMUM LIKELIHOOD ESTIMATORS UNDER RELAXED SMOOTHNESS CONDITIONS ON THE LIKELIHOOD FUNCTION

This report reviews literature on the rate of convergence of maximum likelihood estimators and establishes a Central Limit Theorem, which yields an O(1/sqrt(n)) rate of convergence of the maximum likelihood estimator under somewhat relaxed smoothness conditions. These conditions include the existence of a one-sided derivative in θ of the pdf, compared to up to three that are classically required. A verification through simulation is included in the end of the report.

BIAS-CORRECTED MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETERS OF THE WEIGHTED LINDLEY DISTRIBUTION

This report discusses the calculation of analytic second-order bias techniques for the maximum likelihood estimates (for short, MLEs) of the unknown parameters of the distribution in quality and reliability analysis. It is well-known that the MLEs are widely used to estimate the unknown parameters of the probability distributions due to their various desirable properties; for example, the MLEs are asymptotically unbiased, consistent, and asymptotically normal. However, many of these properties depend on an extremely large sample sizes. Those properties, such as unbiasedness, may not be valid for small or even moderate sample sizes, which are more practical in real data applications. Therefore, some bias-corrected techniques for the MLEs are desired in practice, especially when the sample size is small. Two commonly used popular techniques to reduce the bias of the MLEs, are ‘preventive’ and ‘corrective’ approaches. They both can reduce the bias of the MLEs to order O(n−2), whereas the ‘preventive’ approach does not have an explicit closed form expression. Consequently, we mainly focus on the ‘corrective’ approach in this report. To illustrate the importance of the bias-correction in practice, we apply the bias-corrected method to two popular lifetime distributions: the inverse Lindley distribution and the weighted Lindley distribution. Numerical studies based on the two distributions show that the considered bias-corrected technique is highly recommended over other commonly used estimators without bias-correction. Therefore, special attention should be paid when we estimate the unknown parameters of the probability distributions under the scenario in which the sample size is small or moderate.

Spatio-Temporal Tracking and Phylodynamics of an Urban Dengue 3 Outbreak in Sao Paulo, Brazil

The dengue virus has a single-stranded positive-sense RNA genome of similar to 10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1-4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in Sao Jose do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000-2001. Sixty DENV-3 from Sao Jose do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R(0) = 1.53 and values for lineage 2 of R(0) = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area.

Genetic characterization of St. Louis encephalitis virus isolated from human in São Paulo, Brazil

The molecular characterization of SPH253157, a new strain of St. Louis encephalitis virus (SLEV), isolated in 2004 from the first case of human infection recognized in the state of São Paulo, Brazil, is reported. The patient, presenting a febrile illness without neurological involvement, was hospitalized as a probable case of dengue fever. Genomic RNA was isolated from the supernatant of C6/36 cells infected with acute phase-serum specimen of the patient and the envelope gene was amplified by reverse-transcription-polymerase chain reaction. The complete nucleotide sequence of the envelope gene of this isolate was directly sequenced from the amplified products and compared with other Brazilian and American SLEV strains. Phylogenetic analyses were carried out under maximum likelihood criterion with outgroups both included and excluded. Outgroups comprised four flavivirus of the Japanese encephalitis group. Phylogeny also included Bayesian analysis. The results indicated that the new SLEV isolate belongs to lineage III, being closely related to an Argentinean strain recovered from Culex sp. in 1979. It is concluded that there are at least 3 lineages of SLEV in Brazil.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Evaluación estocástica de huecos de tensión en sistemas eléctricos: estudio de sensibilidad, estimación de índices y localización óptima de medidores

I. GENERALIDADES 1.1. Introducción Entre los diversos tipos de perturbaciones eléctricas, los huecos de tensión son considerados el problema de calidad de suministro más frecuente en los sistemas eléctricos. Este fenómeno es originado por un aumento extremo de la corriente en el sistema, causado principalmente por cortocircuitos o maniobras inadecuadas en la red. Este tipo de perturbación eléctrica está caracterizado básicamente por dos parámetros: tensión residual y duración. Típicamente, se considera que el hueco se produce cuando la tensión residual alcanza en alguna de las fases un valor entre 0.01 a 0.9 pu y tiene una duración de hasta 60 segundos. Para un usuario final, el efecto más relevante de un hueco de tensión es la interrupción o alteración de la operación de sus equipos, siendo los dispositivos de naturaleza electrónica los principalmente afectados (p. ej. ordenador, variador de velocidad, autómata programable, relé, etc.). Debido al auge tecnológico de las últimas décadas y a la búsqueda constante de automatización de los procesos productivos, el uso de componentes electrónicos resulta indispensable en la actualidad. Este hecho, lleva a que los efectos de los huecos de tensión sean más evidentes para el usuario final, provocando que su nivel de exigencia de la calidad de energía suministrada sea cada vez mayor. De forma general, el estudio de los huecos de tensión suele ser abordado bajo dos enfoques: en la carga o en la red. Desde el punto de vista de la carga, se requiere conocer las características de sensibilidad de los equipos para modelar su respuesta ante variaciones súbitas de la tensión del suministro eléctrico. Desde la perspectiva de la red, se busca estimar u obtener información adecuada que permita caracterizar su comportamiento en términos de huecos de tensión. En esta tesis, el trabajo presentado se encuadra en el segundo aspecto, es decir, en el modelado y estimación de la respuesta de un sistema eléctrico de potencia ante los huecos de tensión. 1.2. Planteamiento del problema A pesar de que los huecos de tensión son el problema de calidad de suministro más frecuente en las redes, hasta la actualidad resulta complejo poder analizar de forma adecuada este tipo de perturbación para muchas compañías del sector eléctrico. Entre las razones más comunes se tienen: - El tiempo de monitorización puede llegar a ser de varios años para conseguir una muestra de registros de huecos estadísticamente válida. - La limitación de recursos económicos para la adquisición e instalación de equipos de monitorización de huecos. - El elevado coste operativo que implica el análisis de los datos de los medidores de huecos de tensión instalados. - La restricción que tienen los datos de calidad de energía de las compañías eléctricas. Es decir, ante la carencia de datos que permitan analizar con mayor detalle los huecos de tensión, es de interés de las compañías eléctricas y la academia poder crear métodos fiables que permitan profundizar en el estudio, estimación y supervisión de este fenómeno electromagnético. Los huecos de tensión, al ser principalmente originados por eventos fortuitos como los cortocircuitos, son el resultado de diversas variables exógenas como: (i) la ubicación de la falta, (ii) la impedancia del material de contacto, (iii) el tipo de fallo, (iv) la localización del fallo en la red, (v) la duración del evento, etc. Es decir, para plantear de forma adecuada cualquier modelo teórico sobre los huecos de tensión, se requeriría representar esta incertidumbre combinada de las variables para proveer métodos realistas y, por ende, fiables para los usuarios. 1.3. Objetivo La presente tesis ha tenido como objetivo el desarrollo diversos métodos estocásticos para el estudio, estimación y supervisión de los huecos de tensión en los sistemas eléctricos de potencia. De forma específica, se ha profundizado en los siguientes ámbitos: - En el modelado realista de las variables que influyen en la caracterización de los huecos. Esto es, en esta Tesis se ha propuesto un método que permite representar de forma verosímil su cuantificación y aleatoriedad en el tiempo empleando distribuciones de probabilidad paramétricas. A partir de ello, se ha creado una herramienta informática que permite estimar la severidad de los huecos de tensión en un sistema eléctrico genérico. - Se ha analizado la influencia la influencia de las variables de entrada en la estimación de los huecos de tensión. En este caso, el estudio se ha enfocado en las variables de mayor divergencia en su caracterización de las propuestas existentes. - Se ha desarrollado un método que permite estima el número de huecos de tensión de una zona sin monitorización a través de la información de un conjunto limitado de medidas de un sistema eléctrico. Para ello, se aplican los principios de la estadística Bayesiana, estimando el número de huecos de tensión más probable de un emplazamiento basándose en los registros de huecos de otros nudos de la red. - Plantear una estrategia para optimizar la monitorización de los huecos de tensión en un sistema eléctrico. Es decir, garantizar una supervisión del sistema a través de un número de medidores menor que el número de nudos de la red. II. ESTRUCTURA DE LA TESIS Para plantear las propuestas anteriormente indicadas, la presente Tesis se ha estructurado en seis capítulos. A continuación, se describen brevemente los mismos. A manera de capítulo introductorio, en el capítulo 1, se realiza una descripción del planteamiento y estructura de la presente tesis. Esto es, se da una visión amplia de la problemática a tratar, además de describir el alcance de cada capítulo de la misma. En el capítulo 2, se presenta una breve descripción de los fundamentos y conceptos generales de los huecos de tensión. Los mismos, buscan brindar al lector de una mejor comprensión de los términos e indicadores más empleados en el análisis de severidad de los huecos de tensión en las redes eléctricas. Asimismo, a manera de antecedente, se presenta un resumen de las principales características de las técnicas o métodos existentes aplicados en la predicción y monitorización óptima de los huecos de tensión. En el capítulo 3, se busca fundamentalmente conocer la importancia de las variables que determinen la frecuencia o severidad de los huecos de tensión. Para ello, se ha implementado una herramienta de estimación de huecos de tensión que, a través de un conjunto predeterminado de experimentos mediante la técnica denominada Diseño de experimentos, analiza la importancia de la parametrización de las variables de entrada del modelo. Su análisis, es realizado mediante la técnica de análisis de la varianza (ANOVA), la cual permite establecer con rigor matemático si la caracterización de una determinada variable afecta o no la respuesta del sistema en términos de los huecos de tensión. En el capítulo 4, se propone una metodología que permite predecir la severidad de los huecos de tensión de todo el sistema a partir de los registros de huecos de un conjunto reducido de nudos de dicha red. Para ello, se emplea el teorema de probabilidad condicional de Bayes, el cual calcula las medidas más probables de todo el sistema a partir de la información proporcionada por los medidores de huecos instalados. Asimismo, en este capítulo se revela una importante propiedad de los huecos de tensión, como es la correlación del número de eventos de huecos de tensión en diversas zonas de las redes eléctricas. En el capítulo 5, se desarrollan dos métodos de localización óptima de medidores de huecos de tensión. El primero, que es una evolución metodológica del criterio de observabilidad; aportando en el realismo de la pseudo-monitorización de los huecos de tensión con la que se calcula el conjunto óptimo de medidores y, por ende, en la fiabilidad del método. Como una propuesta alternativa, se emplea la propiedad de correlación de los eventos de huecos de tensión de una red para plantear un método que permita establecer la severidad de los huecos de todo el sistema a partir de una monitorización parcial de dicha red. Finalmente, en el capítulo 6, se realiza una breve descripción de las principales aportaciones de los estudios realizados en esta tesis. Adicionalmente, se describen diversos temas a desarrollar en futuros trabajos. III. RESULTADOS En base a las pruebas realizadas en las tres redes planteadas; dos redes de prueba IEEE de 24 y 118 nudos (IEEE-24 e IEEE-118), además del sistema eléctrico de la República del Ecuador de 357 nudos (EC-357), se describen los siguientes puntos como las observaciones más relevantes: A. Estimación de huecos de tensión en ausencia de medidas: Se implementa un método estocástico de estimación de huecos de tensión denominado PEHT, el cual representa con mayor realismo la simulación de los eventos de huecos de un sistema a largo plazo. Esta primera propuesta de la tesis, es considerada como un paso clave para el desarrollo de futuros métodos del presente trabajo, ya que permite emular de forma fiable los registros de huecos de tensión a largo plazo en una red genérica. Entre las novedades más relevantes del mencionado Programa de Estimación de Huecos de Tensión (PEHT) se tienen: - Considerar el efecto combinado de cinco variables aleatorias de entrada para simular los eventos de huecos de tensión en una pseudo-monitorización a largo plazo. Las variables de entrada modeladas en la caracterización de los huecos de tensión en el PEHT son: (i) coeficiente de fallo, (ii) impedancia de fallo, (iii) tipo de fallo, (iv) localización del fallo y (v) duración. - El modelado estocástico de las variables de entrada impedancia de fallo y duración en la caracterización de los eventos de huecos de tensión. Para la parametrización de las variables mencionadas, se realizó un estudio detallado del comportamiento real de las mismas en los sistemas eléctricos. Asimismo, se define la función estadística que mejor representa la naturaleza aleatoria de cada variable. - Considerar como variables de salida del PEHT a indicadores de severidad de huecos de uso común en las normativas, como es el caso de los índices: SARFI-X, SARFI-Curve, etc. B. Análisis de sensibilidad de los huecos de tensión: Se presenta un estudio causa-efecto (análisis de sensibilidad) de las variables de entrada de mayor divergencia en su parametrización entre las referencias relacionadas a la estimación de los huecos de tensión en redes eléctricas. De forma específica, se profundiza en el estudio de la influencia de la parametrización de las variables coeficiente de fallo e impedancia de fallo en la predicción de los huecos de tensión. A continuación un resumen de las conclusiones más destacables: - La precisión de la variable de entrada coeficiente de fallo se muestra como un parámetro no influyente en la estimación del número de huecos de tensión (SARFI-90 y SARFI-70) a largo plazo. Es decir, no se requiere de una alta precisión del dato tasa de fallo de los elementos del sistema para obtener una adecuada estimación de los huecos de tensión. - La parametrización de la variable impedancia de fallo se muestra como un factor muy sensible en la estimación de la severidad de los huecos de tensión. Por ejemplo, al aumentar el valor medio de esta variable aleatoria, se disminuye considerablemente la severidad reportada de los huecos en la red. Por otra parte, al evaluar el parámetro desviación típica de la impedancia de fallo, se observa una relación directamente proporcional de este parámetro con la severidad de los huecos de tensión de la red. Esto es, al aumentar la desviación típica de la impedancia de fallo, se evidencia un aumento de la media y de la variación interanual de los eventos SARFI-90 y SARFI-70. - En base al análisis de sensibilidad desarrollado en la variable impedancia de fallo, se considera muy cuestionable la fiabilidad de los métodos de estimación de huecos de tensión que omiten su efecto en el modelo planteado. C. Estimación de huecos de tensión en base a la información de una monitorización parcial de la red: Se desarrolla un método que emplea los registros de una red parcialmente monitorizada para determinar la severidad de los huecos de todo el sistema eléctrico. A partir de los casos de estudio realizados, se observa que el método implementado (PEHT+MP) posee las siguientes características: - La metodología propuesta en el PEHT+MP combina la teoría clásica de cortocircuitos con diversas técnicas estadísticas para estimar, a partir de los datos de los medidores de huecos instalados, las medidas de huecos de los nudos sin monitorización de una red genérica. - El proceso de estimación de los huecos de tensión de la zona no monitorizada de la red se fundamenta en la aplicación del teorema de probabilidad condicional de Bayes. Es decir, en base a los datos observados (los registros de los nudos monitorizados), el PEHT+MP calcula de forma probabilística la severidad de los huecos de los nudos sin monitorización del sistema. Entre las partes claves del procedimiento propuesto se tienen los siguientes puntos: (i) la creación de una base de datos realista de huecos de tensión a través del Programa de Estimación de Huecos de Tensión (PEHT) propuesto en el capítulo anterior; y, (ii) el criterio de máxima verosimilitud empleado para estimar las medidas de huecos de los nudos sin monitorización de la red evaluada. - Las predicciones de medidas de huecos de tensión del PEHT+MP se ven potenciadas por la propiedad de correlación de los huecos de tensión en diversas zonas de un sistema eléctrico. Esta característica intrínseca de las redes eléctricas limita de forma significativa la respuesta de las zonas fuertemente correlacionadas del sistema ante un eventual hueco de tensión. Como el PEHT+MP está basado en principios probabilísticos, la reducción del rango de las posibles medidas de huecos se ve reflejado en una mejor predicción de las medidas de huecos de la zona no monitorizada. - Con los datos de un conjunto de medidores relativamente pequeño del sistema, es posible obtener estimaciones precisas (error nulo) de la severidad de los huecos de la zona sin monitorizar en las tres redes estudiadas. - El PEHT+MP se puede aplicar a diversos tipos de indicadores de severidad de los huecos de tensión, como es el caso de los índices: SARFI-X, SARFI-Curve, SEI, etc. D. Localización óptima de medidores de huecos de tensión: Se plantean dos métodos para ubicar de forma estratégica al sistema de monitorización de huecos en una red genérica. La primera propuesta, que es una evolución metodológica de la localización óptima de medidores de huecos basada en el criterio de observabilidad (LOM+OBS); y, como segunda propuesta, un método que determina la localización de los medidores de huecos según el criterio del área de correlación (LOM+COR). Cada método de localización óptima de medidores propuesto tiene un objetivo concreto. En el caso del LOM+OBS, la finalidad del método es determinar el conjunto óptimo de medidores que permita registrar todos los fallos que originen huecos de tensión en la red. Por otro lado, en el método LOM+COR se persigue definir un sistema óptimo de medidores que, mediante la aplicación del PEHT+MP (implementado en el capítulo anterior), sea posible estimar de forma precisa las medidas de huecos de tensión de todo el sistema evaluado. A partir del desarrollo de los casos de estudio de los citados métodos de localización óptima de medidores en las tres redes planteadas, se describen a continuación las observaciones más relevantes: - Como la generación de pseudo-medidas de huecos de tensión de los métodos de localización óptima de medidores (LOM+OBS y LOM+COR) se obtienen mediante la aplicación del algoritmo PEHT, la formulación del criterio de optimización se realiza en base a una pseudo-monitorización realista, la cual considera la naturaleza aleatoria de los huecos de tensión a través de las cinco variables estocásticas modeladas en el PEHT. Esta característica de la base de datos de pseudo-medidas de huecos de los métodos LOM+OBS y LOM+COR brinda una mayor fiabilidad del conjunto óptimo de medidores calculado respecto a otros métodos similares en la bibliografía. - El conjunto óptimo de medidores se determina según la necesidad del operador de la red. Esto es, si el objetivo es registrar todos los fallos que originen huecos de tensión en el sistema, se emplea el criterio de observabilidad en la localización óptima de medidores de huecos. Por otra parte, si se plantea definir un sistema de monitorización que permita establecer la severidad de los huecos de tensión de todo el sistema en base a los datos de un conjunto reducido de medidores de huecos, el criterio de correlación resultaría el adecuado. De forma específica, en el caso del método LOM+OBS, basado en el criterio de observabilidad, se evidenciaron las siguientes propiedades en los casos de estudio realizados: - Al aumentar el tamaño de la red, se observa la tendencia de disminuir el porcentaje de nudos monitorizados de dicho sistema. Por ejemplo, para monitorizar los fallos que originan huecos en la red IEEE-24, se requiere monitorizar el 100\% de los nudos del sistema. En el caso de las redes IEEE-118 y EC-357, el método LOM+OBS determina que con la monitorización de un 89.5% y 65.3% del sistema, respectivamente, se cumpliría con el criterio de observabilidad del método. - El método LOM+OBS permite calcular la probabilidad de utilización del conjunto óptimo de medidores a largo plazo, estableciendo así un criterio de la relevancia que tiene cada medidor considerado como óptimo en la red. Con ello, se puede determinar el nivel de precisión u observabilidad (100%, 95%, etc.) con el cual se detectarían los fallos que generan huecos en la red estudiada. Esto es, al aumentar el nivel de precisión de detección de los fallos que originan huecos, se espera que aumente el número de medidores requeridos en el conjunto óptimo de medidores calculado. - El método LOM+OBS se evidencia como una técnica aplicable a todo tipo de sistema eléctrico (radial o mallado), el cual garantiza la detección de los fallos que originan huecos de tensión en un sistema según el nivel de observabilidad planteado. En el caso del método de localización óptima de medidores basado en el criterio del área de correlación (LOM+COR), las diversas pruebas realizadas evidenciaron las siguientes conclusiones: - El procedimiento del método LOM+COR combina los métodos de estimación de huecos de tensión de capítulos anteriores (PEHT y PEHT+MP) con técnicas de optimización lineal para definir la localización óptima de los medidores de huecos de tensión de una red. Esto es, se emplea el PEHT para generar los pseudo-registros de huecos de tensión, y, en base al criterio planteado de optimización (área de correlación), el LOM+COR formula y calcula analíticamente el conjunto óptimo de medidores de la red a largo plazo. A partir de la información registrada por este conjunto óptimo de medidores de huecos, se garantizaría una predicción precisa de la severidad de los huecos de tensión de todos los nudos del sistema con el PEHT+MP. - El método LOM+COR requiere un porcentaje relativamente reducido de nudos del sistema para cumplir con las condiciones de optimización establecidas en el criterio del área de correlación. Por ejemplo, en el caso del número total de huecos (SARFI-90) de las redes IEEE-24, IEEE-118 y EC-357, se calculó un conjunto óptimo de 9, 12 y 17 medidores de huecos, respectivamente. Es decir, solamente se requeriría monitorizar el 38\%, 10\% y 5\% de los sistemas indicados para supervisar los eventos SARFI-90 en toda la red. - El método LOM+COR se muestra como un procedimiento de optimización versátil, el cual permite reducir la dimensión del sistema de monitorización de huecos de redes eléctricas tanto radiales como malladas. Por sus características, este método de localización óptima permite emular una monitorización integral del sistema a través de los registros de un conjunto pequeño de monitores. Por ello, este nuevo método de optimización de medidores sería aplicable a operadores de redes que busquen disminuir los costes de instalación y operación del sistema de monitorización de los huecos de tensión. ABSTRACT I. GENERALITIES 1.1. Introduction Among the various types of electrical disturbances, voltage sags are considered the most common quality problem in power systems. This phenomenon is caused by an extreme increase of the current in the network, primarily caused by short-circuits or inadequate maneuvers in the system. This type of electrical disturbance is basically characterized by two parameters: residual voltage and duration. Typically, voltage sags occur when the residual voltage, in some phases, reaches a value between 0.01 to 0.9 pu and lasts up to 60 seconds. To an end user, the most important effect of a voltage sags is the interruption or alteration of their equipment operation, with electronic devices the most affected (e.g. computer, drive controller, PLC, relay, etc.). Due to the technology boom of recent decades and the constant search for automating production processes, the use of electronic components is essential today. This fact makes the effects of voltage sags more noticeable to the end user, causing the level of demand for a quality energy supply to be increased. In general, the study of voltage sags is usually approached from one of two aspects: the load or the network. From the point of view of the load, it is necessary to know the sensitivity characteristics of the equipment to model their response to sudden changes in power supply voltage. From the perspective of the network, the goal is to estimate or obtain adequate information to characterize the network behavior in terms of voltage sags. In this thesis, the work presented fits into the second aspect; that is, in the modeling and estimation of the response of a power system to voltage sag events. 1.2. Problem Statement Although voltage sags are the most frequent quality supply problem in electrical networks, thistype of disturbance remains complex and challenging to analyze properly. Among the most common reasons for this difficulty are: - The sag monitoring time, because it can take up to several years to get a statistically valid sample. - The limitation of funds for the acquisition and installation of sag monitoring equipment. - The high operating costs involved in the analysis of the voltage sag data from the installed monitors. - The restrictions that electrical companies have with the registered power quality data. That is, given the lack of data to further voltage sag analysis, it is of interest to electrical utilities and researchers to create reliable methods to deepen the study, estimation and monitoring of this electromagnetic phenomenon. Voltage sags, being mainly caused by random events such as short-circuits, are the result of various exogenous variables such as: (i) the number of faults of a system element, (ii) the impedance of the contact material, (iii) the fault type, (iv) the fault location, (v) the duration of the event, etc. That is, to properly raise any theoretical model of voltage sags, it is necessary to represent the combined uncertainty of variables to provide realistic methods that are reliable for users. 1.3. Objective This Thesis has been aimed at developing various stochastic methods for the study, estimation and monitoring of voltage sags in electrical power systems. Specifically, it has deepened the research in the following areas: - This research furthers knowledge in the realistic modeling of the variables that influence sag characterization. This thesis proposes a method to credibly represent the quantification and randomness of the sags in time by using parametric probability distributions. From this, a software tool was created to estimate the severity of voltage sags in a generic power system. - This research also analyzes the influence of the input variables in the estimation of voltage sags. In this case, the study has focused on the variables of greatest divergence in their characterization of the existing proposals. - A method was developed to estimate the number of voltage sags of an area without monitoring through the information of a limited set of sag monitors in an electrical system. To this end, the principles of Bayesian statistics are applied, estimating the number of sags most likely to happen in a system busbar based in records of other sag network busbars. - A strategy was developed to optimize the monitorization of voltage sags on a power system. Its purpose is to ensure the monitoring of the system through a number of monitors lower than the number of busbars of the network assessed. II. THESIS STRUCTURE To describe in detail the aforementioned proposals, this Thesis has been structured into six chapters. Below is are brief descriptions of them: As an introductory chapter, Chapter 1, provides a description of the approach and structure of this thesis. It presents a wide view of the problem to be treated, in addition to the description of the scope of each chapter. In Chapter 2, a brief description of the fundamental and general concepts of voltage sags is presented to provide to the reader a better understanding of the terms and indicators used in the severity analysis of voltage sags in power networks. Also, by way of background, a summary of the main features of existing techniques or methods used in the prediction and optimal monitoring of voltage sags is also presented. Chapter 3 essentially seeks to know the importance of the variables that determine the frequency or severity of voltage sags. To do this, a tool to estimate voltage sags is implemented that, through a predetermined set of experiments using the technique called Design of Experiments, discusses the importance of the parameters of the input variables of the model. Its analysis is interpreted by using the technique of analysis of variance (ANOVA), which provides mathematical rigor to establish whether the characterization of a particular variable affects the system response in terms of voltage sags or not. In Chapter 4, a methodology to predict the severity of voltage sags of an entire system through the sag logs of a reduced set of monitored busbars is proposed. For this, the Bayes conditional probability theorem is used, which calculates the most likely sag severity of the entire system from the information provided by the installed monitors. Also, in this chapter an important property of voltage sags is revealed, as is the correlation of the voltage sags events in several zones of a power system. In Chapter 5, two methods of optimal location of voltage sag monitors are developed. The first one is a methodological development of the observability criteria; it contributes to the realism of the sag pseudo-monitoring with which the optimal set of sag monitors is calculated and, therefore, to the reliability of the proposed method. As an alternative proposal, the correlation property of the sag events of a network is used to raise a method that establishes the sag severity of the entire system from a partial monitoring of the network. Finally, in Chapter 6, a brief description of the main contributions of the studies in this Thesis is detailed. Additionally, various themes to be developed in future works are described. III. RESULTS. Based on tests on the three networks presented, two IEEE test networks of 24 and 118 busbars (IEEE-24 and IEEE-118) and the electrical system of the Republic of Ecuador (EC-357), the following points present the most important observations: A. Estimation of voltage sags in the absence of measures: A stochastic estimation method of voltage sags, called PEHT, is implemented to represent with greater realism the long-term simulation of voltage sags events in a system. This first proposal of this thesis is considered a key step for the development of future methods of this work, as it emulates in a reliable manner the voltage sag long-term records in a generic network. Among the main innovations of this voltage sag estimation method are the following: - Consideration of the combined effect of five random input variables to simulate the events of voltage sags in long-term monitoring is included. The input variables modeled in the characterization of voltage sags on the PEHT are as follows: (i) fault coefficient, (ii) fault impedance, (iii) type of fault, (iv) location of the fault, and (v) fault duration. - Also included is the stochastic modeling of the input variables of fault impedance and duration in the characterization of the events of voltage sags. For the parameterization of these variables, a detailed study of the real behavior in power systems is developed. Also, the statistical function best suited to the random nature of each variable is defined. - Consideration of sag severity indicators used in standards as PEHT output variables, including such as indices as SARFI-X, SARFI-Curve, etc. B. Sensitivity analysis of voltage sags: A cause-effect study (sensitivity analysis) of the input variables of greatest divergence between reference parameterization related to the estimation of voltage sags in electrical networks is presented. Specifically, it delves into the study of the influence of the parameterization of the variables fault coefficient and fault impedance in the voltage sag estimation. Below is a summary of the most notable observations: - The accuracy of the input variable fault coefficient is shown as a non-influential parameter in the long-term estimation of the number of voltage sags (SARFI-90 and SARFI-70). That is, it does not require a high accuracy of the fault rate data of system elements for a proper voltage sag estimation. - The parameterization of the variable fault impedance is shown to be a very sensitive factor in the estimation of the voltage sag severity. For example, by increasing the average value of this random variable, the reported sag severity in the network significantly decreases. Moreover, in assessing the standard deviation of the fault impedance parameter, a direct relationship of this parameter with the voltage sag severity of the network is observed. That is, by increasing the fault impedance standard deviation, an increase of the average and the interannual variation of the SARFI-90 and SARFI-70 events is evidenced. - Based on the sensitivity analysis developed in the variable fault impedance, the omission of this variable in the voltage sag estimation would significantly call into question the reliability of the responses obtained. C. Voltage sag estimation from the information of a network partially monitored: A method that uses the voltage sag records of a partially monitored network for the sag estimation of all the power system is developed. From the case studies performed, it is observed that the method implemented (PEHT+MP) has the following characteristics: - The methodology proposed in the PEHT+MP combines the classical short-circuit theory with several statistical techniques to estimate, from data the of the installed sag meters, the sag measurements of unmonitored busbars of a generic power network. - The estimation process of voltage sags of the unmonitored zone of the network is based on the application of the conditional probability theorem of Bayes. That is, based on the observed data (monitored busbars records), the PEHT+MP calculates probabilistically the sag severity at unmonitored system busbars. Among the key parts of the proposed procedure are the following: (i) the creation of a realistic data base of voltage sags through of the sag estimation program (PEHT); and, (ii) the maximum likelihood criterion used to estimate the sag indices of system busbars without monitoring. - The voltage sag measurement estimations of PEHT+MP are potentiated by the correlation property of the sag events in power systems. This inherent characteristic of networks significantly limits the response of strongly correlated system zones to a possible voltage sag. As the PEHT+MP is based on probabilistic principles, a reduction of the range of possible sag measurements is reflected in a better sag estimation of the unmonitored area of the power system. - From the data of a set of monitors representing a relatively small portion of the system, to obtain accurate estimations (null error) of the sag severity zones without monitoring is feasible in the three networks studied. - The PEHT+MP can be applied to several types of sag indices, such as: SARFI-X, SARFI-Curve, SEI, etc. D. Optimal location of voltage sag monitors in power systems: Two methods for strategically locating the sag monitoring system are implemented for a generic network. The first proposal is a methodological development of the optimal location of sag monitors based on the observability criterion (LOM + OBS); the second proposal is a method that determines the sag monitor location according to the correlation area criterion (LOM+COR). Each proposed method of optimal location of sag monitors has a specific goal. In the case of LOM+OBS, the purpose of the method is to determine the optimal set of sag monitors to record all faults that originate voltage sags in the network. On the other hand, the LOM+COR method attempts to define the optimal location of sag monitors to estimate the sag indices in all the assessed network with the PEHT+MP application. From the development of the case studies of these methods of optimal location of sag monitors in the three networks raised, the most relevant observations are described below: - As the generation of voltage sag pseudo-measurements of the optimal location methods (LOM+OBS and LOM+COR) are obtained by applying the algorithm PEHT, the formulation of the optimization criterion is performed based on a realistic sag pseudo-monitoring, which considers the random nature of voltage sags through the five stochastic variables modeled in PEHT. This feature of the database of sag pseudo-measurements of the LOM+OBS and LOM+COR methods provides a greater reliability of the optimal set of monitors calculated when compared to similar methods in the bibliography. - The optimal set of sag monitors is determined by the network operator need. That is, if the goal is to record all faults that originate from voltage sags in the system, the observability criterion is used to determine the optimal location of sag monitors (LOM+OBS). Moreover, if the objective is to define a monitoring system that allows establishing the sag severity of the system from taken from information based on a limited set of sag monitors, the correlation area criterion would be appropriate (LOM+COR). Specifically, in the case of the LOM+OBS method (based on the observability criterion), the following properties were observed in the case studies: - By increasing the size of the network, there was observed a reduction in the percentage of monitored system busbars required. For example, to monitor all the faults which cause sags in the IEEE-24 network, then 100% of the system busbars are required for monitoring. In the case of the IEEE-118 and EC-357 networks, the method LOM+OBS determines that with monitoring 89.5 % and 65.3 % of the system, respectively, the observability criterion of the method would be fulfilled. - The LOM+OBS method calculates the probability of using the optimal set of sag monitors in the long term, establishing a relevance criterion of each sag monitor considered as optimal in the network. With this, the level of accuracy or observability (100%, 95%, etc.) can be determined, with which the faults that caused sags in the studied network are detected. That is, when the accuracy level for detecting faults that cause sags in the system is increased, a larger number of sag monitors is expected when calculating the optimal set of monitors. - The LOM + OBS method is demonstrated to be a technique applicable to any type of electrical system (radial or mesh), ensuring the detection of faults that cause voltage sags in a system according to the observability level raised. In the case of the optimal localization of sag monitors based on the criterion of correlation area (LOM+COR), several tests showed the following conclusions: - The procedure of LOM+COR method combines the implemented algorithms of voltage sag estimation (PEHT and PEHT+MP) with linear optimization techniques to define the optimal location of the sag monitors in a network. That is, the PEHT is used to generate the voltage sag pseudo-records, and, from the proposed optimization criterion (correlation area), the LOM+COR formulates and analytically calculates the optimal set of sag monitors of the network in the long term. From the information recorded by the optimal set of sag monitors, an accurate prediction of the voltage sag severity at all the busbars of the system is guaranteed with the PEHT+MP. - The LOM + COR method is shown to be a versatile optimization procedure, which reduces the size of the sag monitoring system both at radial as meshed grids. Due to its characteristics, this optimal location method allows emulation of complete system sag monitoring through the records of a small optimal set of sag monitors. Therefore, this new optimization method would be applicable to network operators that looks to reduce the installation and operation costs of the voltage sag monitoring system.

Biometrical analysis and selection of tetraploid progenies of Panicum maximum using mixed model methods

The objectives of this work were to estimate the genetic and phenotypic parameters and to predict the genetic and genotypic values of the selection candidates obtained from intraspecific crosses in Panicum maximum as well as the performance of the hybrid progeny of the existing and projected crosses. Seventy-nine intraspecific hybrids obtained from artificial crosses among five apomictic and three sexual autotetraploid individuals were evaluated in a clonal test with two replications and ten plants per plot. Green matter yield, total and leaf dry matter yields and leaf percentage were evaluated in five cuts per year during three years. Genetic parameters were estimated and breeding and genotypic values were predicted using the restricted maximum likelihood/best linear unbiased prediction procedure (REML/BLUP). The dominant genetic variance was estimated by adjusting the effect of full-sib families. Low magnitude individual narrow sense heritabilities (0.02-0.05), individual broad sense heritabilities (0.14-0.20) and repeatability measured on an individual basis (0.15-0.21) were obtained. Dominance effects for all evaluated characteristics indicated that breeding strategies that explore heterosis must be adopted. Less than 5% increase in the parameter repeatability was obtained for a three-year evaluation period and may be the criterion to determine the maximum number of years of evaluation to be adopted, without compromising gain per cycle of selection. The identification of hybrid candidates for future cultivars and of those that can be incorporated into the breeding program was based on the genotypic and breeding values, respectively. The prediction of the performance of the hybrid progeny, based on the breeding values of the progenitors, permitted the identification of the best crosses and indicated the best parents to use in crosses.

Test-day milk yield as a selection criterion for dairy buffaloes (Bubalus bubalis Artiodactyla, Bovidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

A note on the likelihood and moments of the skew-normal distribution

In this paper an alternative approach to the one in Henze (1986) is proposed for deriving the odd moments of the skew-normal distribution considered in Azzalini (1985). The approach is based on a Pascal type triangle, which seems to greatly simplify moments computation. Moreover, it is shown that the likelihood equation for estimating the asymmetry parameter in such model is generated as orthogonal functions to the sample vector. As a consequence, conditions for a unique solution of the likelihood equation are established, which seem to hold in more general setting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Genetic associations between age at first calving and heifer body weight and scrotal circumference in Nelore cattle

P>Age at first calving (AFC) measures the entry of heifers into the beef cattle production system. This trait can be used as a selection criterion for earlier reproductive performance. Using data from Nelore cattle participating in the `Program for Genetic Improvement of the Nelore Breed` (PMGRN-Nelore Brazil), bi-trait analyses were performed using the restricted maximum likelihood method, based on an AFC animal model and the following traits: female body weight adjusted to 365 (BW365) and 450 (BW450) days of age, and male scrotal circumference adjusted to 365 (SC365), 450 (SC450), 550 (SC550) and 730 (SC730) days of age. The heritability estimates for AFC ranged from 0.02 +/- 0.02 to 0.04 +/- 0.02. The estimates of additive direct heritabilities (with standard error) for BW365, BW450, SC365, SC450, SC550 and SC730 were 0.36 +/- 0.07, 0.38 +/- 0.07, 0.48 +/- 0.07, 0.65 +/- 0.07, 0.64 +/- 0.07 and 0.42 +/- 0.07, respectively, and the genetic correlations with AFC were -0.38, -0.33, 0.10, -0.13, -0.13 and 0.06, respectively. In the herds studied, selection for SC365, SC450, SC550 or SC730 should not cause genetic changes in AFC. Selection based on BW365 or BW450 would favor smaller AFC breeding values. However, the low magnitude of direct heritability estimates for AFC in these farms indicates that changes in phenotypical expression depend mostly on non-genetic factors.