Distribution-Free Bounds for Serial Correlation Coefficients in Heteroskedastic Symmetric Time Series

We consider the problem of testing whether the observations X1, ..., Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed: exponential bounds, Eaton-type bounds, Chebyshev bounds and Berry-Esséen-Zolotarev bounds. The bounds are exact in finite samples, distribution-free and easy to compute. The performance of the bounds is evaluated and compared with traditional serial dependence tests in a simulation experiment. The procedures proposed are applied to U.S. data on interest rates (commercial paper rate).

A Stable Niche Assumption-Free Test of Ecological Divergence

Understanding the impact of geological events on diversification processes is central to evolutionary ecology. The recent amalgamation between ecological niche models (ENMs) and phylogenetic analyses has been used to estimate historical ranges of modern lineages by projecting current ecological niches of organisms onto paleoclimatic reconstructions. A critical assumption underlying this approach is that niches are stable over time. Using Notophthalmus viridescens (eastern newt), in which four ecologically diverged subspecies are recognized, we introduce an analytical framework free from the niche stability assumption to examine how refugial retreat and subsequent postglacial expansion have affected intraspecific ecological divergence. We found that the current subspecies designation was not congruent with the phylogenetic lineages. Thus, we examined ecological niche overlap between the refugial and modern populations, in both subspecies and lineage, by creating ENMs independently for modern and estimated last glacial maximum (LGM) newt populations, extracting bioclimate variables by randomly generated points, and conducting principal component analyses. Our analyses consistently showed that when tested as a hypothesis, rather than used as an assumption, the niches of N. viridescens lineages have been unstable since the LGM (both subspecies and lineages). There was greater ecological niche differentiation among the subspecies than the modern phylogenetic lineages, suggesting that the subspecies, rather than the phylogenetic lineages, is the unit of the current ecological divergence. The present study found little evidence that the LGM refugial retreat caused the currently observed ecological divergence and suggests that ecological divergence has occurred during postglacial expansion to the current distribution ranges.

An outline of a one semester course on distribution-free statistical inference: hypothesis testing (as given at Columbia University, Autumn 1958)

Mode of access: Internet.

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

A new method for constructing exact tests without making any assumptions

We present a new method for constructing exact distribution-free tests (and confidence intervals) for variables that can generate more than two possible outcomes.This method separates the search for an exact test from the goal to create a non-randomized test. Randomization is used to extend any exact test relating to meansof variables with finitely many outcomes to variables with outcomes belonging to agiven bounded set. Tests in terms of variance and covariance are reduced to testsrelating to means. Randomness is then eliminated in a separate step.This method is used to create confidence intervals for the difference between twomeans (or variances) and tests of stochastic inequality and correlation.

Bringing game theory to hypothesis testing: Establishing finite sample bounds on inference

Small sample properties are of fundamental interest when only limited data is avail-able. Exact inference is limited by constraints imposed by speci.c nonrandomizedtests and of course also by lack of more data. These e¤ects can be separated as we propose to evaluate a test by comparing its type II error to the minimal type II error among all tests for the given sample. Game theory is used to establish this minimal type II error, the associated randomized test is characterized as part of a Nash equilibrium of a .ctitious game against nature.We use this method to investigate sequential tests for the di¤erence between twomeans when outcomes are constrained to belong to a given bounded set. Tests ofinequality and of noninferiority are included. We .nd that inference in terms oftype II error based on a balanced sample cannot be improved by sequential sampling or even by observing counter factual evidence providing there is a reasonable gap between the hypotheses.

Exact tests for correlation and for the slope in simple linear regressions without making assumptions

We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Testing hypotheses in the Birnbaum-Saunders distribution under type-II censored samples

The two-parameter Birnbaum-Saunders distribution has been used successfully to model fatigue failure times. Although censoring is typical in reliability and survival studies, little work has been published on the analysis of censored data for this distribution. In this paper, we address the issue of performing testing inference on the two parameters of the Birnbaum-Saunders distribution under type-II right censored samples. The likelihood ratio statistic and a recently proposed statistic, the gradient statistic, provide a convenient framework for statistical inference in such a case, since they do not require to obtain, estimate or invert an information matrix, which is an advantage in problems involving censored data. An extensive Monte Carlo simulation study is carried out in order to investigate and compare the finite sample performance of the likelihood ratio and the gradient tests. Our numerical results show evidence that the gradient test should be preferred. Further, we also consider the generalized Birnbaum-Saunders distribution under type-II right censored samples and present some Monte Carlo simulations for testing the parameters in this class of models using the likelihood ratio and gradient tests. Three empirical applications are presented. (C) 2011 Elsevier B.V. All rights reserved.

Test systems and mathematical models for transmission network expansion planning

The data of four networks that can be used in carrying out comparative studies with methods for transmission network expansion planning are given. These networks are of various types and different levels of complexity. The main mathematical formulations used in transmission expansion studies-transportation models, hybrid models, DC power flow models, and disjunctive models are also summarised and compared. The main algorithm families are reviewed-both analytical, combinatorial and heuristic approaches. Optimal solutions are not yet known for some of the four networks when more accurate models (e.g. The DC model) are used to represent the power flow equations-the state of the art with regard to this is also summarised. This should serve as a challenge to authors searching for new, more efficient methods.

Determinação de vazões extremas para diversos períodos de retorno para o Rio Paraguai utilizando métodos estatísticos

No presente trabalho foram analisadas as distribuições de probabilidade teórica Normal, Log-Normal, Exponencial, Gama e Weibull, para estimar as vazões máximas e mínimas anuais para o rio Paraguai, utilizando dados de uma estação fluviométrica localizado na cidade de Cáceres-MT. Os testes de Kolmogorov-Smirnov e Qui-Quadrado foram utilizados para verificar a aderência das probabilidades estimadas às freqüências observadas. A série utilizada compreende vazões máximas e mínimas anuais dos anos de 1966 a 2003, excluindo- se dados com falhas. Verificou-se que o melhor ajuste dos valores anuais de vazão máximas e mínimas são referentes a distribuição Gama e Weibull, respectivamente, conforme demonstrado pelo teste de Kolmogorov-Smirnov. Palavras-chave: Previsão de Vazão, teste de aderência.

The local power of the gradient test

The asymptotic expansion of the distribution of the gradient test statistic is derived for a composite hypothesis under a sequence of Pitman alternative hypotheses converging to the null hypothesis at rate n(-1/2), n being the sample size. Comparisons of the local powers of the gradient, likelihood ratio, Wald and score tests reveal no uniform superiority property. The power performance of all four criteria in one-parameter exponential family is examined.

Untersuchungen zur Beteiligung der Preseniline an den molekularen Mechanismen der Amyloid-ß Entstehung

ZusammenfassungMorbus Alzheimer ist eine progressive, neurodegenerative Erkrankung, die weltweit die häufigste Form der Demenz darstellt und im mittleren bis späten Lebensabschnitt auftritt. Die neuropathologischen Merkmale beinhalten das Auftreten von extrazellulären Ablagerungen aus fibrillogenem Aß42 Peptiden in senilen Plaques und intraneuronalen Akkumulationen von hyperphosphoryliertem Tau in sogenannten neurofibrillären Bündeln. Obwohl die meisten Alzheimer Fälle sporadisch und Alters-assoziiert auftreten, gibt es eine autosomal dominant vererbte Form (FAD; Familial Alzheimer Disease), die schon in einem frühen Lebensabschnitt (ab 28 Jahren) ausbrechen kann. Diese aggressive Alzheimer Form wird durch Mutationen im Amyloid-Precursor-Protein-Gen (APP) oder den Presenilin-Genen (PS-1 und PS-2) ausgelöst. Die Presenilin (PS) Proteine sind entscheidend an der Entstehung von Aß beteiligt. So erhöhen FAD-assoziierte Mutationen in PS-1 und PS-2 die Bildung von Aß42. Außerdem verhindern sowohl homozygote PS-1 Null-Mutationen (PS-1-/-) in transgenen Mäusen, als auch dominant negative PS-1 Mutationen in Kulturzellen die Ab Bildung. Diese Belege sprechen für die zur Zeit favorisierte Amyloid Hypothese, in der die toxische Wirkung des Aß-Peptides in der Entstehung der Alzheimer Erkrankung eine zentrale Rolle einnimmt. Die y-Sekretase ist eine Protease, deren Aktivität für die Entstehung von Ab aus dem Vorläuferprotein APP essentiell ist. Damit bildet sie einen möglichen Ansatzpunkt, um grundlegend in den Prozeß der Ab Bildung einzugreifen. Die y-Sekretase ist allerdings noch nicht identifiziert oder kloniert. Es gibt Hinweise, daß die Preseniline y-Sekretase Aktivität besitzen könnten. Diese Theorie ist bis heute jedoch nicht eindeutig belegt. In dieser Arbeit sollten die molekularen Mechanismen der Ab Entstehung und insbesondere die Beteiligung der Preseniline an diesem Prozeß untersucht werden. Dazu wurde zunächst die subzelluläre Verteilung der endogenen Preseniline analysiert. Es konnte erstmalig ein Unterschied in der subzellulären Verteilung zwischen PS-1 und PS-2 festgestellt werden. PS-1 war vorwiegend im ER lokalisiert, wogegen PS-2 stark im Golgi-Apparat angereichert war. Im zweiten Teil der Arbeit wurde nach möglichen Interaktionen der Preseniline mit C-terminalen APP Fragmenten gesucht, die die Substrate der y-Sekretase darstellen. Es konnte gezeigt werden, daß die Preseniline mit einem 21 kDa großen C-terminalen APP Fragment interagieren. Dabei band die Mutante-Form der Preseniline mehr C-terminales APP Fragment als die Wildtyp-Form. Weiterhin wurde ein zellfreies System zur indirekten Bestimmung der y-Sekretase Aktivität etabliert. Mit Hilfe dieses Systems wird es möglich, Inhibitoren der y-Sekretase zu identifizieren. Die Spezifität des zellfreien Testsystems konnte dadurch deutlich gemacht werden, daß das PS-1, das schon in Zellkultur als essentielle Proteinkomponente zur Entstehung von Aß beschrieben wurde, auch in diesem zellfreien y-Sekretase System notwendig war. Allgemeine Proteaseinhibitoren, die alle bekannten Proteasemechanismen abdeckten, zeigten keinen Einfluß auf die de novo Bildung von Aß. Es konnte festgestellt werden, daß neben der y-Sekretase als Aß produzierende Protease auch Aß abbauende Proteasen vorlagen. Das pH-Optimum der y-Sekretase wurde im neutralen Bereich festgestellt. Weiterhin konnte gezeigt werden, daß die y-Sekretase eine transmembrane oder zumindest membranassoziierte Protease ist, die keine cytosolischen Komponenten benötigt.

Tests for Comparing Mark-Specific Hazards and Cumulative Incidence Functions

It is of interest in some applications to determine whether there is a relationship between a hazard rate function (or a cumulative incidence function) and a mark variable which is only observed at uncensored failure times. We develop nonparametric tests for this problem when the mark variable is continuous. Tests are developed for the null hypothesis that the mark-specific hazard rate is independent of the mark versus ordered and two-sided alternatives expressed in terms of mark-specific hazard functions and mark-specific cumulative incidence functions. The test statistics are based on functionals of a bivariate test process equal to a weighted average of differences between a Nelson--Aalen-type estimator of the mark-specific cumulative hazard function and a nonparametric estimator of this function under the null hypothesis. The weight function in the test process can be chosen so that the test statistics are asymptotically distribution-free.Asymptotically correct critical values are obtained through a simple simulation procedure. The testing procedures are shown to perform well in numerical studies, and are illustrated with an AIDS clinical trial example. Specifically, the tests are used to assess if the instantaneous or absolute risk of treatment failure depends on the amount of accumulation of drug resistance mutations in a subject's HIV virus. This assessment helps guide development of anti-HIV therapies that surmount the problem of drug resistance.

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.