Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Peruggia, Mario"'
Bayesian inference with empirical likelihood faces a challenge as the posterior domain is a proper subset of the original parameter space due to the convex hull constraint. We propose a regularized exponentially tilted empirical likelihood to address
Externí odkaz:
http://arxiv.org/abs/2312.17015
Statistical hypotheses are translations of scientific hypotheses into statements about one or more distributions, often concerning their centre. Tests that assess statistical hypotheses of centre implicitly assume a specific centre, e.g., the mean or
Externí odkaz:
http://arxiv.org/abs/2202.12540
Publikováno v:
Journal of Nonparametric Statistics. 35 (2023) 709-732
Empirical likelihood enables a nonparametric, likelihood-driven style of inference without restrictive assumptions routinely made in parametric models. We develop a framework for applying empirical likelihood to the analysis of experimental designs,
Externí odkaz:
http://arxiv.org/abs/2112.09206
The behavior of Bayesian model averaging (BMA) for the normal linear regression model in the presence of influential observations that contribute to model misfit is investigated. Remedies to attenuate the potential negative impacts of such observatio
Externí odkaz:
http://arxiv.org/abs/2103.01252
Topological data analysis (TDA) allows us to explore the topological features of a dataset. Among topological features, lower dimensional ones have recently drawn the attention of practitioners in mathematics and statistics due to their potential to
Externí odkaz:
http://arxiv.org/abs/2006.02568
We discuss the role that the null hypothesis should play in the construction of a test statistic used to make a decision about that hypothesis. To construct the test statistic for a point null hypothesis about a binomial proportion, a common recommen
Externí odkaz:
http://arxiv.org/abs/1907.08703
Publikováno v:
In Econometrics and Statistics July 2023 27:102-119
Autor:
Kunkel, Deborah, Peruggia, Mario
We present an illustrative study in which we use a mixture of regressions model to improve on an ill-fitting simple linear regression model relating log brain mass to log body mass for 100 placental mammalian species. The slope of the model is of par
Externí odkaz:
http://arxiv.org/abs/1905.04389
Autor:
Kunkel, Deborah, Peruggia, Mario
Finite mixtures are a flexible modeling tool for irregularly shaped densities and samples from heterogeneous populations. When modeling with mixtures using an exchangeable prior on the component features, the component labels are arbitrary and are in
Externí odkaz:
http://arxiv.org/abs/1805.08304
Publikováno v:
In Journal of Mathematical Psychology December 2022 111