Journal of statistical theory and practice 

About: Journal of statistical theory and practice is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Estimator & Mathematics. It has an ISSN identifier of 1559-8608. Over the lifetime, 937 publications have been published receiving 5051 citations. The journal is also known as: Statistical theory and practice.

Empirical Evidence on Student-t Log-Returns of Diversified World Stock Indices

Abstract: The aim of this paper is to document some empirical facts related to log-returns of diversified world stock indices when these are denominated in different currencies. Motivated by earlier results, we have obtained the estimated distribution of log-returns for a range of world stock indices over long observation periods. We expand previous studies by applying the maximum likelihood ratio test to the large class of generalized hyperbolic distributions, and investigate the log-returns of a variety of diversified world stock indices in different currency denominations. This identifies the Student-t distribution with about four degrees of freedom as the typical estimated log-return distribution of such indices. Owing to the observed high levels of significance, this result can be interpreted as a stylized empirical fact.

The Gompertz-G family of distributions

Abstract: We introduce and study some general mathematical properties of a new generator of continuous distributions with two extra parameters called the Gompertz-G generator. We present some special models. We investigate the shapes of the density and hazard functions and derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Bonferroni and Lorenz curves, Shannon and Renyi entropies, and order statistics. Two bivariate extensions of this model are proposed. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the potentiality of the new class by means of two real data sets.

Evolutionary Dynamics on Graphs - the Effect of Graph Structure and Initial Placement on Mutant Spread

Abstract: We study the stochastic birth-death process in a finite and structured population and analyze how the fixation probability of a mutant depends on its initial placement. In particular, we study how the fixation probability depends on the degree of the vertex where the mutant is introduced, and which vertices are its neighbours. We find that within a fixed graph, the fixation probability of a mutant has a negative correlation with the degree of the starting vertex. For a general mutant fitness r, we give approximations of relative fixation probabilities in terms of the fixation probabilities of neighbours which will be useful for considering graphs of relatively simple structure but many vertices, for instance of the small world network type, and compare our approximations to simulation results. Further, we explore which types of graphs are conducive to mutant fixation and which are not. We find a high positive correlation between a fixation probability of a randomly placed mutant and the variation...

Median-Based Incremental Cost-Effectiveness Ratio (ICER).

Abstract: Cost-effectiveness analysis (CEA) is a type of economic evaluation that examines the costs and health outcomes of alternative strategies and has been extensively applied in health sciences. The incremental cost-effectiveness ratio (ICER), which represents the additional cost of one unit of outcome gained by one strategy compared with another, has become a popular methodology in CEA. Despite its popularity, limited attention has been paid to summary measures other than the mean for summarizing cost as well as effectiveness in the context of CEA. Although some apparent advantages of other central tendency measures such as median for cost data that are often highly skewed are well understood, thus far, the median has rarely been considered in the ICER. In this paper, we propose the median-based ICER, along with inferential procedures, and suggest that mean and median-based ICERs be considered together as complementary tools in CEA for informed decision making, acknowledging the pros and cons of each. If the mean and median-based CEAs are concordant, we may feel reasonably confident about the cost-effectiveness of an intervention, but if they provide different results, our confidence may need to be adjusted accordingly, pending further evidence.

Bayesian Analysis of Circular Data Using Wrapped Distributions

Abstract: Circular data arise in a number of different areas such as geological, meteorological, biological and industrial sciences Standard statistical techniques can not be used to model circular data due to the circular geometry of the sample space One of the common methods to analyze circular data is known as the wrapping approach This approach is based on a simple fact that a probability distribution on a circle can be obtained by wrapping a probability distribution defined on the real line A large class of probability distributions that are flexible to account for different features of circular data can be obtained by the aforementioned approach However, the likelihood-based inference for wrapped distributions can be very complicated and computationally intensive The EM algorithm to compute the MLE is feasible, but is computationally unsatisfactory A data augmentation method using slice sampling is proposed to overcome such computational difficulties The proposed method turns out to be flexible and computationally efficient to fit a wide class of wrapped distributions In addition, a new model selection criteria for circular data is developed Results from an extensive simulation study are presented to validate the performance of the proposed estimation method and the model selection criteria Application to a real data set is also presented and parameter estimates are compared to those that are available in the literature