Alternative ways to estimate change points in multinomial sequences. An application to an authorship attribution problem

The statistical analysis of literary style is the part of stylometry that compares measurable characteristics in a text that are rarely controlled by the author, with those in other texts. When the goal is to settle authorship questions, these characteristics should relate to the author’s style and not to the genre, epoch or editor, and they should be such that their variation between authors is larger than the variation within comparable texts from the same author. For an overview of the literature on stylometry and some of the techniques involved, see for example Mosteller and Wallace (1964, 82), Herdan (1964), Morton (1978), Holmes (1985), Oakes (1998) or Lebart, Salem and Berry (1998). Tirant lo Blanc, a chivalry book, is the main work in catalan literature and it was hailed to be “the best book of its kind in the world” by Cervantes in Don Quixote. Considered by writters like Vargas Llosa or Damaso Alonso to be the first modern novel in Europe, it has been translated several times into Spanish, Italian and French, with modern English translations by Rosenthal (1996) and La Fontaine (1993). The main body of this book was written between 1460 and 1465, but it was not printed until 1490. There is an intense and long lasting debate around its authorship sprouting from its first edition, where its introduction states that the whole book is the work of Martorell (1413?-1468), while at the end it is stated that the last one fourth of the book is by Galba (?-1490), after the death of Martorell. Some of the authors that support the theory of single authorship are Riquer (1990), Chiner (1993) and Badia (1993), while some of those supporting the double authorship are Riquer (1947), Coromines (1956) and Ferrando (1995). For an overview of this debate, see Riquer (1990). Neither of the two candidate authors left any text comparable to the one under study, and therefore discriminant analysis can not be used to help classify chapters by author. By using sample texts encompassing about ten percent of the book, and looking at word length and at the use of 44 conjunctions, prepositions and articles, Ginebra and Cabos (1998) detect heterogeneities that might indicate the existence of two authors. By analyzing the diversity of the vocabulary, Riba and Ginebra (2000) estimates that stylistic boundary to be near chapter 383. Following the lead of the extensive literature, this paper looks into word length, the use of the most frequent words and into the use of vowels in each chapter of the book. Given that the features selected are categorical, that leads to three contingency tables of ordered rows and therefore to three sequences of multinomial observations. Section 2 explores these sequences graphically, observing a clear shift in their distribution. Section 3 describes the problem of the estimation of a suden change-point in those sequences, in the following sections we propose various ways to estimate change-points in multinomial sequences; the method in section 4 involves fitting models for polytomous data, the one in Section 5 fits gamma models onto the sequence of Chi-square distances between each row profiles and the average profile, the one in Section 6 fits models onto the sequence of values taken by the first component of the correspondence analysis as well as onto sequences of other summary measures like the average word length. In Section 7 we fit models onto the marginal binomial sequences to identify the features that distinguish the chapters before and after that boundary. Most methods rely heavily on the use of generalized linear models

Option pricing in market models driven by telegraph processes with jumps

Esta tesis está dividida en dos partes: en la primera parte se presentan y estudian los procesos telegráficos, los procesos de Poisson con compensador telegráfico y los procesos telegráficos con saltos. El estudio presentado en esta primera parte incluye el cálculo de las distribuciones de cada proceso, las medias y varianzas, así como las funciones generadoras de momentos entre otras propiedades. Utilizando estas propiedades en la segunda parte se estudian los modelos de valoración de opciones basados en procesos telegráficos con saltos. En esta parte se da una descripción de cómo calcular las medidas neutrales al riesgo, se encuentra la condición de no arbitraje en este tipo de modelos y por último se calcula el precio de las opciones Europeas de compra y venta.

Flight periodicity and the vertical distribution of high-altitude moth migration over southern Britain

The continuous operation of insect-monitoring radars in the UK has permitted, for the first time, the characterization of various phenomena associated with high-altitude migration of large insects over this part of northern Europe. Previous studies have taken a case-study approach, concentrating on a small number of nights of particular interest. Here, combining data from two radars, and from an extensive suction- and light-trapping network, we have undertaken a more systematic, longer-term study of diel flight periodicity and vertical distribution of macro-insects in the atmosphere. Firstly, we identify general features of insect abundance and stratification, occurring during the 24-hour cycle, which emerge from four years’ aggregated radar data for the summer months in southern Britain. These features include mass emigrations at dusk and to a lesser extent at dawn, and daytime concentrations associated with thermal convection. We then focus our attention on the well-defined layers of large nocturnal migrants that form in the early evening, usually at heights of 200–500 m above ground. We present evidence from both radar and trap data that these nocturnal layers are composed mainly of noctuid moths, with species such as Noctua pronuba, Autographa gamma, Agrotis exclamationis, A. segetum, Xestia c-nigrum and Phlogophora meticulosa predominating.

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

Diagnosis of variability and trends in a global precipitation dataset using a physically motivated statistical model

A physically motivated statistical model is used to diagnose variability and trends in wintertime ( October - March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasi-geostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity q(s) has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.

Generalized beta generated distributions

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entropy to the centre of the parent distribution. This parameter controls skewness without necessarily differentiating tail weights. The GBG class also has tractable properties: we present various expansions for moments, generating function and quantiles. The model parameters are estimated by maximum likelihood and the usefulness of the new class is illustrated by means of some real data sets.

Sequence analysis and distribution in Salmonella enterica serovars of IS3-like elements

The genome of Salmonella enterica serovar Enteritidis was shown to possess three IS3-like insertion elements, designated IS1230A, B and C, and each was cloned and their respective deoxynucleotide sequences determined. Mutations in elements IS1230A and B resulted in frameshifts in the open reading frames that encoded a putative transposase to be inactive. IS1230C was truncated at nucleotide 774 relative to IS1230B and therefore did not possess the 3' terminal inverted repeat. The three IS1230 derivatives were closely related to each other based on nucleotide sequence similarity. IS1230A was located adjacent to the sef operon encoding SEF14 fimbriae located at minute 97 of the genome of S. Enteritidis. IS1230B was located adjacent to the umuDC operon at minute 42.5 on the genome, itself located near to one terminus of an 815-kb genome inversion of S. Enteritidis relative to S. Typhimurium. IS1230C was located next to attB, the bacteriophage P22 attachment site, and proB, encoding gamma-glutamyl phosphate reductase. A truncated 3' remnant of IS1230, designated IS1230T, was identified in a clinical isolate of S. Typhimurium DT193 strain 2391. This element was located next to attB adjacent to which were bacteriophage P22-like sequences. Southern hybridisation of total genomic DNA from eighteen phage types of S. Enteritidis and eighteen definitive types of S. Typhimurium showed similar, if not identical, restriction fragment profiles in the respective serovars when probed with IS1230A.

Describing seasonal variability in the distribution of daily effective temperatures for 1985-2009 compared to 1904-1984 for De Bilt, Holland

This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.

Constraints on the spectral distribution of energy and enstrophy dissipation in forced two-dimensional turbulence

We study two-dimensional (2D) turbulence in a doubly periodic domain driven by a monoscale-like forcing and damped by various dissipation mechanisms of the form νμ(−Δ)μ. By “monoscale-like” we mean that the forcing is applied over a finite range of wavenumbers kmin≤k≤kmax, and that the ratio of enstrophy injection η≥0 to energy injection ε≥0 is bounded by kmin2ε≤η≤kmax2ε. Such a forcing is frequently considered in theoretical and numerical studies of 2D turbulence. It is shown that for μ≥0 the asymptotic behaviour satisfies ∥u∥12≤kmax2∥u∥2, where ∥u∥2 and ∥u∥12 are the energy and enstrophy, respectively. If the condition of monoscale-like forcing holds only in a time-mean sense, then the inequality holds in the time mean. It is also shown that for Navier–Stokes turbulence (μ=1), the time-mean enstrophy dissipation rate is bounded from above by 2ν1kmax2. These results place strong constraints on the spectral distribution of energy and enstrophy and of their dissipation, and thereby on the existence of energy and enstrophy cascades, in such systems. In particular, the classical dual cascade picture is shown to be invalid for forced 2D Navier–Stokes turbulence (μ=1) when it is forced in this manner. Inclusion of Ekman drag (μ=0) along with molecular viscosity permits a dual cascade, but is incompatible with the log-modified −3 power law for the energy spectrum in the enstrophy-cascading inertial range. In order to achieve the latter, it is necessary to invoke an inverse viscosity (μ<0). These constraints on permissible power laws apply for any spectrally localized forcing, not just for monoscale-like forcing.

Peroxisome proliferator-activated receptor-gamma co-activator-1alpha (PGC-1alpha) gene polymorphisms and their relationship to Type 2 diabetes in Asian Indians

AIMS: The objective of the present investigation was to examine the relationship of three polymorphisms, Thr394Thr, Gly482Ser and +A2962G, of the peroxisome proliferator activated receptor-gamma co-activator-1 alpha (PGC-1alpha) gene with Type 2 diabetes in Asian Indians. METHODS: The study group comprised 515 Type 2 diabetic and 882 normal glucose tolerant subjects chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in southern India. The three polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Haplotype frequencies were estimated using an expectation-maximization (EM) algorithm. Linkage disequilibrium was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms studied were not in linkage disequilibrium. With respect to the Thr394Thr polymorphism, 20% of the Type 2 diabetic patients (103/515) had the GA genotype compared with 12% of the normal glucose tolerance (NGT) subjects (108/882) (P = 0.0004). The frequency of the A allele was also higher in Type 2 diabetic subjects (0.11) compared with NGT subjects (0.07) (P = 0.002). Regression analysis revealed the odds ratio for Type 2 diabetes for the susceptible genotype (XA) to be 1.683 (95% confidence intervals: 1.264-2.241, P = 0.0004). Age adjusted glycated haemoglobin (P = 0.003), serum cholesterol (P = 0.001) and low-density lipoprotein (LDL) cholesterol (P = 0.001) levels and systolic blood pressure (P = 0.001) were higher in the NGT subjects with the XA genotype compared with GG genotype. There were no differences in genotype or allelic distribution between the Type 2 diabetic and NGT subjects with respect to the Gly482Ser and +A2962G polymorphisms. CONCLUSIONS: The A allele of Thr394Thr (G --> A) polymorphism of the PGC-1 gene is associated with Type 2 diabetes in Asian Indian subjects and the XA genotype confers 1.6 times higher risk for Type 2 diabetes compared with the GG genotype in this population.

Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Effects of 15-deoxy-Delta(12, 14) prostaglandin J(2) and ciglitazone on human cancer cell cycle progression and death: The role of PPAR gamma

The role of PPAR-gamma in ciglitazone and 15-d PGJ(2)-induced apoptosis and cell cycle arrest of Jurkat (before and after PPAR gamma gene silencing), U937 (express high levels of PPAR gamma) and HeLa (that express very low levels of PPAR gamma) cells was investigated. PPAR gamma gene silencing, per se, induced a G2/M cell arrest, loss of membrane integrity and DNA fragmentation of Jurkat cells, indicating that PPAR gamma is important for this cell survival and proliferation. Ciglitazone-induced apoptosis was abolished after knockdown of PPAR gamma suggesting a PPAR gamma-dependent pro-apoptotic effect. However, ciglitazone treatment was toxic for U937 and HeLa cells regardless of the presence of PPAR gamma. This treatment did not change the cell cycle distribution corroborating with a PPAR gamma-independent mechanism. On the other hand, 15-d PGJ(2) induced apoptosis of the three cancer cell lines regardless of the expression of PPAR gamma. These results suggest that PPAR gamma plays an important role for death of malignant T lymphocytes (Jurkat cells) and PPAR gamma agonists exert their effects through PPAR gamma-dependent and -independent mechanisms depending on the drug and the cell type. (C) 2007 Elsevier B.V. All rights reserved.

The novel ruthenium-gamma-linolenic complex [Ru(2)(aGLA)(4)Cl] inhibits C6 rat glioma cell proliferation and induces changes in mitochondrial membrane potential, increased reactive oxygen species generation and apoptosis in vitro

The present study reports the synthesis of a novel compound with the formula [Ru(2)(aGLA)(4)Cl] according to elemental analyses data, referred to as Ru(2)GLA. The electronic spectra of Ru(2)GLA is typical of a mixed valent diruthenium(II,III) carboxylate. Ru(2)GLA was synthesized with the aim of combining and possibly improving the anti-tumour properties of the two active components ruthenium and gamma-linolenic acid (GLA). The properties of Ru(2)GLA were tested in C6 rat glioma cells by analysing cell number, viability, lipid droplet formation, apoptosis, cell cycle distribution, mitochondrial membrane potential and reactive oxygen species. Ru(2)GLA inhibited cell proliferation in a time and concentration dependent manner. Nile Red staining suggested that Ru(2)GLA enters the cells and ICP-AES elemental analysis found all increase in ruthenium from <0.02 to 425 mg/Kg in treated cells. The sub-G1 apoptotic cell population was increased by Ru(2)GLA (22 +/- 5.2%) when analysed by FACS and this was confirmed by Hoechst staining of nuclei. Mitochondrial membrane potential was decreased in the presence of Ru(2)GLA (44 +/- 2.3%). In contrast, the cells which maintained a high mitochondrial membrane potential had an increase (18 +/- 1.5%) in reactive oxygen species generation. Both decreased mitochondrial membrane potential and increased reactive oxygen species generation may be involved in triggering apoptosis in Ru(2)GLA exposed cells. The EC(50) for Ru(2)GLA decreased with increasing time of exposure from 285 mu M at 24h, 211 mu M at 48 h to 81 mu M at 72 h. In conclusion, Ru(2)GLA is a novel drug with anti proliferative properties in C6 glioma cells and is a potential candidate for novel therapies in gliomas. Copyright (C) 2009 John Wiley & Sons, Ltd.

A Bayesian Analysis in the Presence of Covariates for Multivariate Survival Data: An example of Application

In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different ""frailties"" or latent variables are considered to capture the correlation among the survival times for the same individual. We assume Weibull or generalized Gamma distributions considering right censored lifetime data. We develop the Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.