1,720,961 research outputs found
An EM-based iterative method for solving large sparse linear systems
No full textWe propose a novel iterative algorithm for solving a large sparse linear system. The method is based on the EM algorithm. If the system has a unique solution, the algorithm guarantees convergence with a geometric rate. Otherwise, convergence to a minimal Kullback–Leibler divergence point is guaranteed. The algorithm is easy to code and competitive with other iterative algorithms.11Nsciescopu
A Closer Look at the Personality-Turnover Relationship: Criterion Expansion, Dark Traits, and Time
No full textRecent advances in the personality and turnover literatures suggest the importance of expanding current turnover criteria, incorporating dark personality traits, and examining the role of time in these relationships. The present study investigates these issues by considering both the speed and the reasons for leaving, examining a wider range of personality variables as predictors by including both “bright” and “dark” traits, and exploring the potential moderating effect of time in such predictions. Data were collected from a sample of 617 employees working in an electronics manufacturing firm in the United States. Using a Bayesian survival analysis framework, we found that dark traits were just as useful in predicting turnover outcomes as traditional personality traits and best predicted the specific turnover reasons, “deviant behavior” and “no call no show.” Investigating the role of time showed that job satisfaction and intellectual curiosity (i.e., Openness) grew in predictive strength over the course of organizational tenure but that the time-dependent effects of other predictors were negligible. © 2016, The Author(s) 2016.11Nssciscopu
Bayesian sparse linear regression with unknown symmetric error
No full textWe study Bayesian procedures for sparse linear regression when the unknown error distribution is endowed with a non-parametric prior. Specifically, we put a symmetrized Dirichlet process mixture of Gaussian prior on the error density, where the mixing distributions are compactly supported. For the prior on regression coefficients, a mixture of point masses at zero and continuous distributions is considered. Under the assumption that the model is well specified, we study behavior of the posterior with diverging number of predictors. The compatibility and restricted eigenvalue conditions yield the minimax convergence rate of the regression coefficients in ℓ1- and ℓ2-norms, respectively. In addition, strong model selection consistency and a semi-parametric Bernstein–von Mises theorem are proven under slightly stronger conditions.11Nscopu
On an algorithm for solving Fredholm integrals of the first kind
No full textIn this paper we use an iterative algorithm for solving Fredholm equations of the first kind. The basic algorithm and convergence properties are known under certain conditions, but we provide a simpler convergence proof without requiring the restrictive conditions that have previously been needed. Several examples of independent interest are given, including mixing density estimation and a first passage time density function involving Brownian motion. We also develop the basic algorithm to include functions which are not necessarily non-negative and, again, present illustrations.11Nsciescopu
A mixture of beta–Dirichlet processes prior for Bayesian analysis of event history data
No full textIn this paper, we propose a mixture of beta-Dirichlet processes as a nonparametric prior for the cumulative intensity functions of a Markov process. This family of priors is a natural extension of a mixture of Dirichlet processes or a mixture of beta processes which are devised to compromise advantages of parametric and nonparametric approaches. They give most of their prior mass to the small neighborhood of a specific parametric model. We show that a mixture of beta Dirichlet processes prior is conjugate with Markov processes. Formulas for computing the posterior distribution are derived. Finally, results of analyzing credit history data are given. (C) 2012 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.11Nsciescopuskc
An online gibbs sampler algorithm for hierarchical dirichlet processes prior
No full textThe hierarchical Dirichlet processes (HDP) is a Bayesian nonparametric model that provides a flexible mixed-membership to documents. In this paper, we develop a novel mini-batch online Gibbs sampler algorithm for the HDP which can be easily applied to massive and streaming data. For this purpose, a new prior process so called the generalized hierarchical Dirichlet processes (gHDP) is proposed. The gHDP is an extension of the standard HDP where some prespecified topics can be included in the top-level Dirichlet process. By analyzing various datasets, we show that the proposed mini-batch online Gibbs sampler algorithm performs significantly better than the online variational algorithm for the HDP. © Springer International Publishing AG 2016.11Nscopu
The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors
Get PDFIn a smooth semi-parametric model, the marginal posterior distribution of a finite-dimensional parameter of interest is expected to be asymptotically equivalent to the sampling distribution of any efficient point estimator. This assertion leads to asymptotic equivalence of the credible and confidence sets of the parameter of interest, and is known as the semi-parametric Bernstein-von Mises theorem. In recent years, this theorem has received much attention and has been widely applied. Here, we consider models in which errors with symmetric densities play a role. Specifically, we show that the marginal posterior distributions of the regression coefficients in linear regression and linear mixed-effect
models satisfy the semi-parametric Bernstein-von Mises assertion. As a result,
Bayes estimators in these models achieve frequentist inferential optimality, as expressed, for example, in H´ajek’s convolution and asymptotic minimax theorems.
For the prior on the space of error densities, we provide two well-known examples, namely, the Dirichlet process mixture of normal densities and random series priors. The results provide efficient estimates of the regression coefficients in the linear mixed-effect model, for which no efficient point estimators currently exist.11Nsciescopu
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
