Exponentiality Test Based on the Progressive Type II Censoring via Cumulative Entropy

In this article, we use cumulative residual Kullback-Leibler information (CRKL) and cumulative Kullback-Leibler information (CKL) to construct two goodness-of-fit test statistics for testing exponentiality with progressively Type-II censored data. The power of the proposed tests are compared with the power of goodness-of-fit test for exponentiality introduced by Balakrishnan et al. (2007 Balakrishnan, N., Habibi Rad, A., Arghami, N.R. (2007). Testing exponentiality based on Kullback-Leibler information with progressively type-II censored data. IEEE Transactions on Reliability 56(2):301–307.[Crossref], [Web of Science ®] , [Google Scholar]). We show that when the hazard function of the alternative is monotone decreasing, the test based on CRKL has higher power and when the hazard function of the alternative is non-monotone, the test based on CKL has higher power. But, when it is monotone increasing the power difference between test based on CKL and their proposed test is not so remarkable. The use of the proposed tests is shown in an illustrative example.     

Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence

Most existing reduced-form macroeconomic multivariate time series models employ elliptical disturbances, so that the forecast densities produced are symmetric. In this article, we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry. Empirical and skew t distributions are employed for the margins, and a high-dimensional Gaussian copula is used to jointly capture cross-sectional and (multivariate) serial dependence. The copula parameter matrix is given by the correlation matrix of a latent stationary and Markov vector autoregression (VAR). We show that the likelihood can be evaluated efficiently using the unique partial correlations, and estimate the copula using Bayesian methods. We examine the forecasting performance of the model for four U.S. macroeconomic variables between 1975:Q1 and 2011:Q2 using quarterly real-time data. We find that the point and density forecasts from the copula model are competitive with those from a Bayesian VAR. During the recent recession the forecast densities exhibit substantial asymmetry, avoiding some of the pitfalls of the symmetric forecast densities from the Bayesian VAR. We show that the asymmetries in the predictive distributions of GDP growth and inflation are similar to those found in the probabilistic forecasts from the Survey of Professional Forecasters. Last, we find that unlike the linear VAR model, our fitted Gaussian copula models exhibit nonlinear dependencies between some macroeconomic variables. This article has online supplementary material.     

Stochastically optimal bootstrap sample size for shrinkage-type statistics

In nonregular problems where the conventional \(n\) out of \(n\) bootstrap is inconsistent, the \(m\) out of \(n\) bootstrap provides a useful remedy to restore consistency. Conventionally, optimal choice of the bootstrap sample size \(m\) is taken to be the minimiser of a frequentist error measure, estimation of which has posed a major difficulty hindering practical application of the \(m\) out of \(n\) bootstrap method. Relatively little attention has been paid to a stronger, stochastic, version of the optimal bootstrap sample size, defined as the minimiser of an error measure calculated directly from the observed sample. Motivated by this stronger notion of optimality, we develop procedures for calculating the stochastically optimal value of \(m\). Our procedures are shown to work under special forms of Edgeworth-type expansions which are typically satisfied by statistics of the shrinkage type. Theoretical and empirical properties of our methods are illustrated with three examples, namely the James–Stein estimator, the ridge regression estimator and the post-model-selection regression estimator.     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.     

“It has given me life.” Latinas and the U-Visa: A Qualitative Study

Women, particularly undocumented women, are at an increased risk for gender-based violence including intimate partner violence (IPV). Women’s lack of legal immigration status is often used as a tool of dominance and control of undocumented women. The Victim of Trafficking and Violence Prevention Act 2000 created the U-Visa that provides undocumented IPV victims with lawful immigration status if they are willing to assist authorities in investigating crimes. The objective of this study is to better understand the benefits of obtaining the U-Visa from the perspectives of Latina U-Visa recipients who are survivors of IPV. In this community-based qualitative research study involving IPV survivors, community leaders, service providers and academics, we collected qualitative data through interviews with 20 participants including 15 survivors of IPV who were U-Visa recipients. Interviews were digitally-recorded, transcribed and translated, and analyzed using a qualitative software to develop key themes. Women received a $20 gift card as a token of appreciation for their participation in this study. Findings highlight key benefits such as improved mental health, renewed confidence and self-esteem, self-confidence, less perceived exploitation, access to better jobs and housing, freedom to travel, and improved economic and social well-being for visa recipients and their families. Obtaining the U-Visa was a transformative and life-changing experience for Latina survivors of IPV. Social policies such as TVPA help support vulnerable women who are victims of IPV.     

Caught between different worlds: how transgendered women may be "forced" into risky sex

We qualitatively explored reasons why transgendered women may engage in sexual risk that could lead to HIV infection. Specifically, we conducted this investigation with transgendered women identifying as Black/African American. Interviews from 17 participants were audio taped and analyzed. Four themes emerged. Women commonly reported they had a strong need/desire to be loved by men. Many stated they had and would engage in unprotected sex to obtain and preserve such a relationship. Nearly all were currently using female hormones. Nine obtained their hormones through non-medical means including the Internet, transgendered friends, and street vendors. For these women hormone injections often involved sharing needles/syringes. Selling sex was a common practice and many women did so without the benefit of condom use. Finally, women experienced multiple forms of societal discrimination. By being caught between worlds (straight, gay, male, and female) transgendered women may be placed into situations where avoiding HIV risk is extremely difficult.     

Domestic violence screening and service acceptance among adult victims in a dependency court setting

Many child welfare systems are unable to effectively identify and address co-occurring domestic violence and child maltreatment. In response, the Dependency Court Intervention Program for Family Violence implemented a protocol to identify indicators of domestic violence in families involved with child protection proceedings. This article highlights data that demonstrate the ability of an outreach and screening process to identify adult victims of domestic violence in dependency court and to offer them appropriate intervention services.