Journal•ISSN: 0167-7152
Statistics & Probability Letters
Elsevier BV
About: Statistics & Probability Letters is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Estimator & Random variable. It has an ISSN identifier of 0167-7152. Over the lifetime, 8965 publications have been published receiving 117077 citations. The journal is also known as: Statistics & Statistix.
Papers published on a yearly basis
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TL;DR: This article introduced the idea of Bayesian quantile regression employing a likelihood function that is based on the asymmetric Laplace distribution, which is a natural and effective way to model quantile regressions.
773 citations
TL;DR: In this paper, an estimator of the number of change points in an independent normal sequence is proposed via Schwarz' criterion, and weak consistency of this estimator is established; however, it is not shown that the estimator can be used to estimate change points.
641 citations
TL;DR: In this article, an estimator of regression by means of a functional principal component analysis analogous to the one introduced by Bosq in the case of Hilbertian AR processes was proposed and both convergence in probability and almost sure convergence of this estimator are stated.
539 citations
TL;DR: In this paper, the concepts location, scatter, skewness and kurtosis of multivariate distributions are studied and measures of these properties are introduced which include some new generalizations of well-known univariate statistics.
462 citations
TL;DR: In this article, a distribution-free multivariate Kolmogorov-Smirnov goodness-of-fit test is presented, which uses a statistic which is built using Rosenblatt's transformation.
456 citations