A new class of modified binomial distributions with applications to certain toxicological experiments ∗

A large class of distributions is proposed to fit the binary data obtained from certain toxicological experiments in which, for example, the outcome of interest is the occurrence of dead or malformed fetuses in a litter. This class of distribution includes the additive model proposed by Altham (1978) as a special case. The fits to three real-life data sets using this new distribution are shown to be much better than those provided by beta-binomial distribution used by Williams (1975) and by the correlated-binomial distribution proposed by Kupper and Haseman (1978).     

A SINGLE CHANNEL ON/OFF MODEL WITH TCP-LIKE CONTROL

We model behavior of a TCP-like source transmitting over a single channel to a server that processes work at a constant rate τ. Transmission by the source follows an on/off mechanism. When the overall load in the system is below a critical constant γ, transmission rates increase linearly but when the load exceeds γ, then transmission rates decrease geometrically fast. We study the system by means of an embedded Markov chain, which gives the buffer content at the start of transmissions. Attention is paid to the time necessary to transmit a file of size L and both the tail behavior and expectation of the distribution of file transmission time are considered.     

Various measures of dependence of a new asymmetric generalized Farlie–Gumbel–Morgenstern copulas

ABSTRACT

In this paper, we discuss an asymmetric extension of Farlie–Gumbel–Morgenstern copulas studied by several authors and obtain the range of the parameter. We derive an expression for regression function and the properties of these copulas are studied in detail. Also, explicit expressions for various measures of association are obtained. These measures are numerically compared for some particular parametric values of the copulas.     

Estimating the Hurst parameter in financial time series via heuristic approaches

This research investigates long memory financial equity markets using three heuristic methodologies namely a proposed modified variance time-aggregated plot, modified rescaled-range plot and periodogram approaches. The intensity of the long memory process is quantified in terms of Hurst parameter (H). Five Malaysian equity market indices are selected in the empirical studies with the inclusion of pre- and post-drastic economic events. Our empirical results evidenced dissimilar long memory behaviours in the different regimes of significant economic events. It is also found that after the short-memory adjustment, all the equity markets exhibited substantial reductions in long memory estimations.     

Testing for Choice Dynamics in Panel Data

This article applies different approaches to distinguish state dependence from unobserved heterogeneity and serial correlation and, hence, test for state dependence in consumer brand choices. First, we apply a simple method proposed by Chamberlain, which involves lagged exogenous variables only. Second, we also estimate a lagged-dependent-variable specification proposed by Wooldridge. Third, we use the estimation approach suggested by Wooldridge to estimate a model with both lagged dependent and exogenous variables to distinguish between the two different sources of choice dynamics, state dependence and lagged effects of the exogenous variables. Our analysis reveals that the best approach is to use models with both lagged dependent and exogenous variables. Our findings include strong evidence for state dependence in five out of the six product categories studied in this article.     

Computing functional estimators of spatiotemporal long-range dependence parameters in the spectral-wavelet domain

This paper addresses the problem of parameter estimation of spatiotemporal long-range dependence models from functional spectral data. Four wavelet-based functional estimation algorithms are proposed to approximate the multidimensional strong-dependence parameter, characterizing the covariance tail behavior of the spatiotemporal non-self-similar model class studied in [Frías et al., 2006b] and [Frías et al., 2009]. Wavelet regression is performed in all of them. Functional spectral data are averaged in the first and fourth algorithms, while, in the second and third ones, averaging is performed on the wavelet regression estimates. Smoothing over the wavelet translation parameter is performed, within each resolution level, only in Algorithms 3 and 4. A simulation study is carried out to illustrate the performance of the four functional estimation algorithms proposed under different scenarios.     

Self-Esteem and Risky Behaviors Among Residents of a Tanzanian Sugar Plantation: A Brief Report

ABSTRACT

Risky behaviors can increase acquisition risk of HIV and other sexually transmitted infections (STI). Self-esteem may be linked to risky behavior, but little research has assessed this relationship in low-resource regions. Using cross-sectional data from a study of Tanzanian plantation residents, the authors examined associations between self-esteem and two risky behaviors (problematic alcohol use and transactional sex). In unadjusted and adjusted analyses, higher self-esteem was significantly associated with less prevalent transactional sex (adjusted prevalence ratio [aPR]: 0.74, 95% confidence interval [CI]: 0.59–0.93) and less prevalent problematic alcohol use (aPR: 0.81, 95% CI:0.70–0.93). Self-esteem may be an appropriate target for STI prevention interventions.     

Bayesian inference for the proportion of true null hypotheses using minimum Hellinger distance

It is important that the proportion of true null hypotheses be estimated accurately in a multiple hypothesis context. Current estimation methods, however, are not suitable for high-dimensional data such as microarray data. First, they do not consider the (strong) dependence between hypotheses (or genes), thereby resulting in inaccurate estimation. Second, the unknown distribution of false null hypotheses cannot be estimated properly by these methods. Third, the estimation is affected strongly by outliers. In this paper, we find out the optimal procedure for estimating the proportion of true null hypotheses under a (strong) dependence based on the Dirichlet process prior. In addition, by using the minimum Hellinger distance, the estimation should be robust to any model misspecification as well as to any outliers while maintaining efficiency. The results are confirmed by a simulation study, and the newly developed methodology is illustrated by a real microarray data.     

Constructing Copulas with Given Diagonal and Opposite Diagonal Sections

A method for constructing copulas with given diagonal and opposite diagonal sections is presented. It makes use of a recently developed method for constructing cross-copulas with given horizontal and vertical sections. Conditions guaranteeing the existence of a cross-copula with the given diagonal and opposite diagonal sections are derived. It is shown how the new method facilitates the construction of families of copulas that simultaneously model tail dependences of upper-upper, upper-lower, lower-lower and lower-upper type.     

A class of copulas with piecewise linear horizontal sections

We introduce the class of bivariate copulas with piecewise linear horizontal sections whose graph is composed, at most, of two segments. It is a wide class of copulas which contains some known copulas. We study several properties of the copulas in the new class concerning absolute continuity, singular components, measures of association, concordance ordering, dependence concepts and symmetry. Finally, we provide several examples.