Two-Sided Generalized Exponential Distribution

We derive a generalization of the exponential distribution by making log transformation of the standard two-sided power distribution. We show that this new generalization is in fact a mixture of a truncated exponential distribution and truncated generalized exponential distribution introduced by Gupta and Kundu [Generalized exponential distributions. Aust. N. Z. J. Stat. 41(1999):173–188]. The newly defined distribution is more flexible for modeling data than the ordinary exponential distribution. We study its properties, estimate the parameters, and demonstrate it on some well-known real data sets comparing other existing methods.     

Equivalence of parametric identifiability and estimability

Given that estimators are monotone functions of observations, parametric identiflability is shown to be both necessary and sufficient for estimability.     

Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models

In this paper, efficient importance sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate stochastic volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as well as simulation smoothing where the latent volatilities are sampled at once. Based on this EIS simulation smoother, a Bayesian Markov chain Monte Carlo (MCMC) posterior analysis of the parameters of SV models can be performed.     

The ARL of modified Shewhart control charts for conditionally heteroskedastic models

In this article we consider the modified Shewhart control chart for ARCH processes and introduce it for threshold ARCH (TARCH) ones. For both charts, we determine bounds for the distribution of the in-control run length (RL) and, consequently, for its average (ARL), both depending only on the distribution of the generating white noise, the model parameters and the critical value. For the ARCH model, we compare our bounds with others available in literature and show how they improve the existing ones. We present a simulation study to assess the quality of the bounds calculated for the ARL.     

The Working Families’ Tax Credit and Some European Tax Reforms in A Collective Setting

A framework for simplified implementation of the collective model of labor supply decisions is presented in the context of fiscal reforms in the UK. Through its collective form the model accounts for the well known problem of distribution between wallet and purse, a broadly debated issue which has so far been impossible to model due to the limitations of the unitary model of household behavior. A calibrated data set is used to model the effects of introducing two forms of the Working Families’ Tax Credit. We also summarize results of estimations and calibrations obtained using the same methodology on data from five other European countries. The results underline the importance of taking account of the intrahousehold decision process and suggest that who receives government transfers does matter from the point of view of labor supply and welfare of household members. They also highlight the need for more research into models of household behavior.

Collective Models of Labor Supply with Nonconvex Budget Sets and Nonparticipation: A Calibration Approach

We suggest a methodology to calibrate a collective model with household-specific bargaining rules and marriage-specific preferences that incorporate leisure externalities. The empirical identification relies on the assumption that some aspects of individual preferences remain the same after marriage, so that estimation on single individuals can be used. The procedure maps the complete Pareto frontier of each household in the dataset and we define alternative measures of a power index. The latter is then regressed on relevant bargaining factors, including a set of variables retracing the potential relative contributions of the spouses to household disposable income. In its capacity to handle complex budget sets and labor force participation decisions of both spouses, this framework allows the comparison of unitary and collective predictions of labor supply reactions and welfare changes entailed by fiscal reforms in a realistic setting (see Michal Myck et al., 2006; Denis Beninger et al., 2006).

Sample size for estimating a binomial proportion: comparison of different methods

The poor performance of the Wald method for constructing confidence intervals (CIs) for a binomial proportion has been demonstrated in a vast literature. The related problem of sample size determination needs to be updated and comparative studies are essential to understanding the performance of alternative methods. In this paper, the sample size is obtained for the Clopper–Pearson, Bayesian (Uniform and Jeffreys priors), Wilson, Agresti–Coull, Anscombe, and Wald methods. Two two-step procedures are used: one based on the expected length (EL) of the CI and another one on its first-order approximation. In the first step, all possible solutions that satisfy the optimal criterion are obtained. In the second step, a single solution is proposed according to a new criterion (e.g. highest coverage probability (CP)). In practice, it is expected a sample size reduction, therefore, we explore the behavior of the methods admitting 30% and 50% of losses. For all the methods, the ELs are inflated, as expected, but the coverage probabilities remain close to the original target (with few exceptions). It is not easy to suggest a method that is optimal throughout the range (0, 1) for p. Depending on whether the goal is to achieve CP approximately or above the nominal level different recommendations are made.     

Bayesian inference for quantum state tomography

We present a Bayesian approach to the problem of estimating density matrices in quantum state tomography. A general framework is presented based on a suitable mathematical formulation, where a study of the convergence of the Monte Carlo Markov Chain algorithm is given, including a comparison with other estimation methods, such as maximum likelihood estimation and linear inversion. This analysis indicates that our approach not only recovers the underlying parameters quite properly, but also produces physically acceptable punctual and interval estimates. A prior sensitive study was conducted indicating that when useful prior information is available and incorporated, more accurate results are obtained. This general framework, which is based on a reparameterization of the model, allows an easier choice of the prior and proposal distributions for the Metropolis–Hastings algorithm.     

Matrix mean squared error comparisons of some biased estimators with two biasing parameters

To deal with multicollinearity problem, the biased estimators with two biasing parameters have recently attracted much research interest. The aim of this article is to compare one of the last proposals given by Yang and Chang (2010 Yang, H., and X. Chang. 2010. A new two-parameter estimator in linear regression. Communications in Statistics: Theory and Methods 39 (6):923–34.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) with Liu-type estimator (Liu 2003 Liu, K. 2003. Using Liu-type estimator to combat collinearity. Communications in Statistics: Theory and Methods 32 (5):1009–20.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) and k ? d class estimator (Sakallioglu and Kaciranlar 2008 Sakallioglu, S., and S. Kaciranlar. 2008. A new biased estimator based on ridge estimation. Statistical Papers 49:669–89.[Crossref], [Web of Science ®] , [Google Scholar]) under the matrix mean squared error criterion. As well as giving these comparisons theoretically, we support the results with the extended simulation studies and real data example, which show the advantages of the proposal given by Yang and Chang (2010 Yang, H., and X. Chang. 2010. A new two-parameter estimator in linear regression. Communications in Statistics: Theory and Methods 39 (6):923–34.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) over the other proposals with increasing multicollinearity level.     

Development of the Sexual Five-Facet Mindfulness Questionnaire (FFMQ-S): Validation Among a Community Sample of French-Speaking Women

It has been recently demonstrated that mindfulness-based intervention may be particularly suitable for addressing sexual difficulties in women. Although the Five-Facet Mindfulness Questionnaire (FFMQ) is currently one of the most widely used scales to assess mindfulness, no adaptation and validation of the FFMQ to measure female sexual functioning has been published. The main aim of this study was to develop and validate a sexual version of the Five Facets Mindfulness Questionnaire (FFMQ-S) to specifically measure mindfulness in the context of sexual encounters. A total of 251 healthy, French-speaking female volunteers were administered the FFMQ-S, the original FFMQ, and the Female Sexual Distress Scale (FSDS-R). Confirmatory factor analyses indicated that the FFMQ-S exhibits a five-factor model, as implied by the original FFMQ. Good scale reliability was observed. The FFMQ-S showed significant correlations with the FSDS-R and the usual FFMQ. Scores on the FFMQ-S correlated significantly more negatively with the total FSDS-R score than with the total score of the original version of the FFMQ. These findings clearly support the relevance of developing a version of the FFMQ tailored to sexual functioning.