FDR control of detected regions by multiscale matched filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multiscale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal-to-noise ratio via matched filtering. This is achieved by considering a one-dimensional region detection problem as its equivalent zero-dimensional peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the nonzero regions is known a priori, e.g., rectangular pulse, the signal regions can also be reconstructed from the detected peaks, seen as their topological point representatives. Simulations show that the method can effectively perform signal detection and reconstruction in the simulated data under high noise conditions, while controlling the FDR of detected regions and their reconstructed length.     

Estimating function method for product autoregressive models

The first-order product autoregressive (PAR(1)) model introduced by McKenzie in 1982 McKenzie, E. D. (1982). Product autoregression: A time series characterization of the gamma distribution. Journal of Applied Probability 19:463–468. [Google Scholar] did not attract the attention of practitioners due to the unavailability of a proper estimation method. This article proposes an estimating function (EF) method to fill the gap. In particular, we suggest an optimal combination of linear and quadratic EFs to overcome the problem of parameter identification. The procedure is applied to Weibull and Gamma PAR(1) models. Simulation and data analysis show that the proposed method performs better than the existing methods.     

Effects of some design factors on the distribution of similarity indices in cluster analysis

This article investigates the effects of number of clusters, cluster size, and correction for chance agreement on the distribution of two similarity indices, namely, Jaccard and Rand indices. Skewness and kurtosis are calculated for the two indices and their corrected forms then compared with those of the normal distribution. Three clustering algorithms are implemented: complete linkage, Ward, and K-means. Data were randomly generated from bivariate normal distributions with specified means and variance covariance matrices. Three-way ANOVA is performed to assess the significance of the design factors using skewness and kurtosis of the indices as responses. Test statistics for testing skewness and kurtosis and observed power are calculated. Simulation results showed that independent of the clustering algorithms or the similarity indices used, the interaction effect cluster size x number of clusters and the main effects of cluster size and number of clusters were found always significant for skewness and kurtosis. The three way interaction of cluster size x correction x number of clusters was significant for skewness of Rand and Jaccard indices using all clustering algorithms, but was not significant using Ward's method for both Rand and Jaccard indices, while significant for Jaccard only using complete linkage and K-means algorithms. The correction for chance agreement was significant for skewness and kurtosis using Rand and Jaccard indices when complete linkage method is used. Hence, such design factors must be taken into consideration when studying distribution of such indices.     

Weighted kappa as a function of unweighted kappas

The kappa coefficient is a widely used measure for assessing agreement on a nominal scale. Weighted kappa is an extension of Cohen's kappa that is commonly used for measuring agreement on an ordinal scale. In this article, it is shown that weighted kappa can be computed as a function of unweighted kappas. The latter coefficients are kappa coefficients that correspond to smaller contingency tables that are obtained by merging categories.     

Bayesian prediction of order statistics with fixed and random sample sizes based on k-record values from Pareto distribution

In this paper, the two-parameter Pareto distribution is considered and the problem of prediction of order statistics from a future sample and that of its geometric mean are discussed. The Bayesian approach is applied to construct predictors based on observed k-record values for the cases when the future sample size is fixed and when it is random. Several Bayesian prediction intervals are derived. Finally, the results of a simulation study and a numerical example are presented for illustrating all the inferential procedures developed here.     

On fiducial generators

Fiducial inference has been gaining presence recently and it is the intention of the present article to look at the notion of fiducial generators; meaning procedures to simulate parameter values that in some sense correspond to simulations from some implicit fiducial distribution. It is well known that when the distribution has group structure, stemming from the natural pivotal associated, a fiducial may be obtained. It is in the non group distributions that there appears to be still room for finding a fiducial distribution. Recently some general procedures have been proposed for dealing with generalized fiducials, but these depend on certain choices for a structural equation or a fiducial equation, as in Hannig (2009 Hannig, J. (2009). On generalized fiducial inference. Stat. Sin. 19:491–544.[Web of Science ®] , [Google Scholar]) or Taraldsen and Lindqvist (2013 Taraldsen, G., Lindqvist, B.H. (2013). Fiducial theory and optimal inference. Ann. Stat. 41(1):323–341.[Crossref], [Web of Science ®] , [Google Scholar]), respectively. A brief presentation is made of an earlier approach to fiducial inference for multivariate parameters, as in Brillinger (1962 Brillinger, D.R. (1962). Examples bearing on the definition of fiducial probability with a bibliography. Ann. Math. Stat. 33(4):1349–1355.[Crossref] , [Google Scholar]), and the implied fiducial generator introduced in Engen and Lillegård (1997 Engen, S., Lillegård, M. (1997). Stochastic simulation conditioned on sufficient statistics. Biometrika 84(1):235–240.[Crossref], [Web of Science ®] , [Google Scholar]), trying to connect them. Three interesting non group distributions are seen; two of them, the truncated exponential and the two-parameter gamma, already reported in literature. A third non group distribution is analyzed; the inverse Gaussian, connecting the fiducial that results following Brillinger (1962 Brillinger, D.R. (1962). Examples bearing on the definition of fiducial probability with a bibliography. Ann. Math. Stat. 33(4):1349–1355.[Crossref] , [Google Scholar]), with a result pertaining confidence limits for the shape parameter in Hsieh (1990 Hsieh, H.K. (1990). Inferences on the coefficient of variation of an inverse-Gaussian distribution. Commun. Stat. - Theory Methods 19(5):1589–1605.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). In the three cases, comparisons are made with the Bayesian posteriors that have been known to be close numerically. Some discussion is made on the issue of singularities of the fiducial density and its connection with densities that do not integrate to unity. As to the case of discrete observables, some comments are made for the Bernoulli distribution, only.     

How Does Occupational Access for Older Workers Differ by Education?

To assess the employment opportunities of older job-changers in the years prior to retirement, this study examines the how the breadth of occupations in which they find employment narrows as they age past their prime working years and how this differs by gender and educational attainment. The results indicate that workers who change jobs in their early 50s find employment in a reasonably similar set of occupations as prime-age workers, with opportunities narrowing at older ages. They also indicate that job opportunities broadened significantly for better-educated older workers since the late 1990s. While job opportunities now narrow significantly for less-educated men in their late 50s, this narrowing primarily occurs in the early 60s for women and better-educated men. In contrast to previous research, the study finds that employer policies that emphasize hiring from within are less important barriers to the hiring of older job-seekers. The study also finds that the narrowing of job opportunities is associated with a general decline in job quality as measured by median occupational earnings, a decline associated with differences in occupational skill requirements and the underlying economic environment. These results suggest that older hiring is not as limited to a select few occupations as it had been in previous decades, and that policy reforms aimed at increasing opportunities and improving labor market fluidity might best be served if they focused on less-educated men.     

Concealed Ownership: Americans’ Perceived Comfort Sharing Gun Ownership Status with Others

While much is known about how Americans feel about guns and gun control policy, less is known about how Americans perceive gun owners, or how gun owners and nonowners view themselves. The present study examines how comfortable individuals feel disclosing their gun ownership status with family, friends, coworkers, employers, doctors, teachers, police, and strangers. This article uses stigma theory as a guiding framework. Data were obtained from a nationwide survey conducted in February 2016 of more than 250 current gun owners and more than 250 nonowners. Analyses utilize ordered logistic regression. Findings show that whites, older Americans, and those with more pro-gun attitudes express more comfort sharing whether they own a gun. Respondents also indicate that familiarity with the individual requesting gun ownership information and concern over how that person might react are key factors that affect comfort with disclosure. Implications and directions for future research are discussed.     

Sexual orientation differences in HIV testing motivation among college men

Objective: To investigate sexual orientation differences in college men's motivations for HIV testing. Participants: 665 male college students in the Southeastern United States from 2006 to 2014. Methods: Students completed a survey on HIV risk factors and testing motivations. Logistic regressions were conducted to determine the differences between heterosexual men (HM) and sexual minority men (SMM). Results: SMM were more motivated to get tested by concern over past condomless sex, while HM were more often cited supporting the testing program “on principle” and wanting a free t-shirt. SMM and HM differed in behaviors that impact HIV risk and other demographics. However, differences in testing motivation by concern over past condomless sex or wanting a free t-shirt persisted when controlling for these demographic and behavioral differences. Conclusions: Appropriately designed HIV prevention interventions on college campuses should target SMM's distinct concern over past condomless sex as a testing motivation.     

Alcohol use and strenuous physical activity in college students: A longitudinal test of 2 explanatory models of health behavior

Objective: To help clarify the effect of gender on the bidirectional relationship between alcohol use and strenuous physical activity in college students. Participants: Five hundred twenty-four (52% female) college students recruited in August 2008 and 2009 and followed up in April 2009 and April 2011, respectively. Methods: Participants reported their alcohol use and strenuous physical activity on 2 occasions (baseline and follow-up) spaced approximately 1 or 2 years apart. Results: For females, alcohol use quantity at baseline was associated with increased strenuous physical activity at 1- and 2-year follow-ups, and alcohol use frequency at baseline was associated with decreased strenuous physical activity at 2-year follow-up. For males, alcohol use frequency at baseline predicted decreased strenuous physical activity at 1-year follow-up. Conclusions: Gender differences may be explained from an eating disorders perspective such that women use physical activity as a compensatory strategy to combat potential weight gain from calories consumed during alcohol use.