A method for using random parameters in analyzing permanent sample plots

Summary

Uncertainty analysis based on sensitivity applied to angle-ply composite structures

This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.

Integration of geometric consistency contributory factors in three-leg junctions collision prediction models of Portuguese two-lane national highways

This paper aims at developing a collision prediction model for three-leg junctions located in national roads (NR) in Northern Portugal. The focus is to identify factors that contribute for collision type crashes in those locations, mainly factors related to road geometric consistency, since literature is scarce on those, and to research the impact of three modeling methods: generalized estimating equations, random-effects negative binomial models and random-parameters negative binomial models, on the factors of those models. The database used included data published between 2008 and 2010 of 177 three-leg junctions. It was split in three groups of contributing factors which were tested sequentially for each of the adopted models: at first only traffic, then, traffic and the geometric characteristics of the junctions within their area of influence; and, lastly, factors which show the difference between the geometric characteristics of the segments boarding the junctionsâ area of influence and the segment included in that area were added. The choice of the best modeling technique was supported by the result of a cross validation made to ascertain the best model for the three sets of researched contributing factors. The models fitted with random-parameters negative binomial models had the best performance in the process. In the best models obtained for every modeling technique, the characteristics of the road environment, including proxy measures for the geometric consistency, along with traffic volume, contribute significantly to the number of collisions. Both the variables concerning junctions and the various national highway segments in their area of influence, as well as variations from those characteristics concerning roadway segments which border the already mentioned area of influence have proven their relevance and, therefore, there is a rightful need to incorporate the effect of geometric consistency in the three-leg junctions safety studies.

Model selection for the mixed logit with Bayesian estimation

In this paper, the mixed logit (ML) using Bayesian methods was employed to examine willingness-to-pay (WTP) to consume bread produced with reduced levels of pesticides so as to ameliorate environmental quality, from data generated by a choice experiment. Model comparison used the marginal likelihood, which is preferable for Bayesian model comparison and testing. Models containing constant and random parameters for a number of distributions were considered, along with models in ‘preference space’ and ‘WTP space’ as well as those allowing for misreporting. We found: strong support for the ML estimated in WTP space; little support for fixing the price coefficient a common practice advocated and adopted in the environmental economics literature; and, weak evidence for misreporting.

Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Resposta individual à ingestão de treonina para suínos em fase de crescimento

Pós-graduação em Zootecnia - FCAV

Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking

The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Análisis paramétrico determinista y aleatorio de problemas dinámicos en estructuras aeroespaciales

Los fenómenos dinámicos pueden poner en peligro la integridad de estructuras aeroespaciales y los ingenieros han desarrollado diferentes estrategias para analizarlos. Uno de los grandes problemas que se plantean en la ingeniería es cómo atacar un problema dinámico estructural. En la presente tesis se plantean distintos fenómenos dinámicos y se proponen métodos para estimar o simular sus comportamientos mediante un análisis paramétrico determinista y aleatorio del problema. Se han propuesto desde problemas sencillos con pocos grados de libertad que sirven para analizar las diferentes estrategias y herramientas a utilizar, hasta fenómenos muy dinámicos que contienen comportamientos no lineales, daños y fallos. Los primeros ejemplos de investigación planteados cubren una amplia gama de los fenómenos dinámicos, como el análisis de vibraciones de elementos másicos, incluyendo impactos y contactos, y el análisis de una viga con carga armónica aplicada a la que también se le añaden parámetros aleatorios que pueden responder a un desconocimiento o incertidumbre de los mismos. Durante el desarrollo de la tesis se introducen conceptos y se aplican distintos métodos, como el método de elementos finitos (FEM) en el que se analiza su resolución tanto por esquemas implícitos como explícitos, y métodos de análisis paramétricos y estadísticos mediante la técnica de Monte Carlo. Más adelante, una vez ya planteadas las herramientas y estrategias de análisis, se estudian fenómenos más complejos, como el impacto a baja velocidad en materiales compuestos, en el que se busca evaluar la resistencia residual y, por lo tanto, la tolerancia al daño de la estructura. Se trata de un suceso que puede producirse por la caída de herramienta, granizo o restos en la pista de aterrizaje. Otro de los fenómenos analizados también se da en un aeropuerto y se trata de la colisión con un dispositivo frangible, el cual tiene que romperse bajo ciertas cargas y, sin embargo, soportar otras. Finalmente, se aplica toda la metodología planteada en simular y analizar un posible incidente en vuelo, el fenómeno de la pérdida de pala de un turbohélice. Se trata de un suceso muy particular en el que la estructura tiene que soportar unas cargas complejas y excepcionales con las que la aeronave debe ser capaz de completar con éxito el vuelo. El análisis incluye comportamientos no lineales, daños, y varios tipos de fallos, y en el que se trata de identificar los parámetros clave en la secuencia del fallo. El suceso se analiza mediante análisis estructurales deterministas más habituales y también mediante otras técnicas como el método de Monte Carlo con el que se logran estudiar distintas incertidumbres en los parámetros con variables aleatorias. Se estudian, entre otros, el tamaño de pala perdida, la velocidad y el momento en el que se produce la rotura, y la rigidez y resistencia de los apoyos del motor. Se tiene en cuenta incluso el amortiguamiento estructural del sistema. Las distintas estrategias de análisis permiten obtener unos resultados valiosos e interesantes que han sido objeto de distintas publicaciones. ABSTRACT Dynamic phenomena can endanger the integrity of aerospace structures and, consequently, engineers have developed different strategies to analyze them. One of the major engineering problems is how to deal with the structural dynamics. In this thesis, different dynamic phenomena are introduced and several methods are proposed to estimate or simulate their behaviors. The analysis is considered through parametric, deterministic and statistical methods. The suggested issues are from simple problems with few degrees of freedom, in order to develop different strategies and tools to solve them, to very dynamic phenomena containing nonlinear behaviors failures, damages. The first examples cover a wide variety of dynamic phenomena such as vibration analysis of mass elements, including impacts and contacts, and beam analysis with harmonic load applied, in which random parameters are included. These parameters can represent the unawareness or uncertainty of certain variables. During the development of the thesis several concepts are introduced and different methods are applied, such as the finite element method (FEM), which is solved through implicit and explicit schemes, and parametrical and statistical methods using the Monte Carlo analysis technique. Next, once the tools and strategies of analysis are set out more complex phenomena are studied. This is the case of a low-speed impact in composite materials, the residual strength of the structure is evaluated, and therefore, its damage tolerance. This incident may occur from a tool dropped, hail or debris throw on the runway. At an airport may also occur, and it is also analyzed, a collision between an airplane and a frangible device. The devise must brake under these loads, however, it must withstand others. Finally, all the considered methodology is applied to simulate and analyze a flight incident, the blade loss phenomenon of a turboprop. In this particular event the structure must support complex and exceptional loads and the aircraft must be able to successfully complete the flight. Nonlinear behavior, damage, and different types of failures are included in the analysis, in which the key parameters in the failure sequence are identified. The incident is analyzed by deterministic structural analysis and also by other techniques such as Monte Carlo method, in which it is possible to include different parametric uncertainties through random variables. Some of the evaluated parameters are, among others, the blade loss size, propeller rotational frequency, speed and angular position where the blade is lost, and the stiffness and strength of the engine mounts. The study does also research on the structural damping of the system. The different strategies of analysis obtain valuable and interesting results that have been already published.

Testing reference dependence, loss aversion and diminishing sensitivity in Spanish tourism

Based on Tversky and Kahneman’s Prospect Theory, we test the existence of reference dependence, loss aversion and diminishing sensitivity in Spanish tourism. To do this, we incorporate the reference-dependent model into a Multinomial Logit Model with Random Parameters -which controls for heterogeneity- and apply it to a sample of vacation choices made by Spaniards. We find that the difference between reference price and actual price is considered to make decisions, confirming that reference dependence exists; that people react more strongly to price increases than to price decreases relative to their reference price, which represents evidence in favor of the loss aversion phenomenon; and that there is diminishing sensitivity for losses only, showing convexity for these negative values.

Direct versus indirect channels: Differentiated loss aversion in a high‐involvement, non‐frequently purchased hedonic product

Purpose – This article aims to investigate whether intermediaries reduce loss aversion in the context of a high-involvement non-frequently purchased hedonic product (tourism packages). Design/methodology/approach – The study incorporates the reference-dependent model into a multinomial logit model with random parameters, which controls for heterogeneity and allows representation of different correlation patterns between non-independent alternatives. Findings – Differentiated loss aversion is found: consumers buying high-involvement non-frequently purchased hedonic products are less loss averse when using an intermediary than when dealing with each provider separately and booking their services independently. This result can be taken as identifying consumer-based added value provided by the intermediaries. Practical implications – Knowing the effect of an increase in their prices is crucial for tourism collective brands (e.g. “sun and sea”, “inland”, “green destinations”, “World Heritage destinations”). This is especially applicable nowadays on account of the fact that many destinations have lowered prices to attract tourists (although, in the future, they will have to put prices back up to their normal levels). The negative effect of raising prices can be absorbed more easily via indirect channels when compared to individual providers, as the influence of loss aversion is lower for the former than the latter. The key implication is that intermediaries can – and should – add value in competition with direct e-tailing. Originality/value – Research on loss aversion in retailing has been prolific, exclusively focused on low-involvement and frequently purchased products without distinguishing the direct or indirect character of the distribution channel. However, less is known about other types of products such as high-involvement non-frequently purchased hedonic products. This article focuses on the latter and analyzes different patterns of loss aversion in direct and indirect channels.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.

An implementation of genetic algorithms as a basis for a trading system on the foreign exchange market

Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process is very helpful. In this paper, we try to create such a system with a genetic algorithm engine to emulate trader behaviour on the foreign exchange market and to find the most profitable trading strategy.

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.