Hasil untuk "math.ST"

Alexander R. Pruss

A simple integral representation involving no derivatives or continuity assumptions is given for proper single-event scoring rules.

Nicolas Marie

This paper deals with a consistent estimator of the multifunction involved in a time-discretized Skorokhod reflection problem defined by a stochastic differential equation and a Moreau sweeping process.

Mahdi Mollakazemiha

This paper introduces a mathematical framework of a stochastic process model as a generalization of diffusion stochastic processes to model latent variables in categorical responses given unobserved random effects and maximum likelihood estimation of parameters is indicated.

Mathias Drton, Hongjian Shi, David Strieder

Invited discussion for Stat of "A note on universal inference" by Timmy Tse and Anthony Davison (2022)

Edith Gabriel, Joël Chadoeuf

In this note we consider non-stationary cluster point processes and we derive their conditional intensity, i.e. the intensity of the process given the locations of one or more events of the process. We then provide some approximations of the conditional intensity.

Xiongzhi Chen

We prove a strong law of large numbers for simultaneously testing parameters of a large number of dependent, Lancaster bivariate random variables with infinite supports, and discuss its implications.

Nick Kloodt

The so far most general identification result in the context of nonparametric transformation models is proven. The result is constructive in the sense that it provides an explicit expression of the transformation function.

Sonja Petrović

This short piece defines a Markov basis. The aim is to introduce the statistical concept to mathematicians.

Guillaume Chauvet

Midzuno sampling enables to estimate ratios unbiasedly. We prove the asymptotic normality for estimators of totals and ratios under Midzuno sampling. We also propose consistent variance estimators.

Arnaud Poinas

We prove a general inequality on $β$-mixing coefficients of point processes depending uniquely on their $n$-th order intensity functions. We apply this inequality in the case of determinantal point processes and show that the rate of decay of the $β$-mixing coefficients of a wide class of DPPs is optimal.

Mark Ebden

A gentle introduction to Gaussian processes (GPs). The three parts of the document consider GPs for regression, classification, and dimensionality reduction.

James V. Zidek

Comment on Article by Ferreira and Gamerman [arXiv:1509.03410].

Mohamed Cherfi

This paper is devoted to robust estimation based on dual divergences estimators for parametric models in the framework of right censored data. We give limit laws of the proposed estimators and examine their asymptotic properties through a simulation study.

Jose A. Diaz-Garcia, Ramon Gutierrez-Jaimez

In this work it is propose an alterative proof of one of basic properties of the zonal polynomials. This identity is generalised for the Jack polynomials.

Andrew Gelman

We review some approaches and philosophies of causal inference coming from sociology, economics, computer science, cognitive science, and statistics

Ya'acov Ritov

The paper argues that a part of the current statistical discussion is not based on the standard firm foundations of the field. Among the examples we consider are prediction into the future, semi-supervised classification, and causality inference based on observational data.

Yo Sheena, Akimichi Takemura

An admissible estimator of the eigenvalues of the variance-covariance matrix is given for multivariate normal distributions with respect to the scale-invariant squared error loss.

Nicolas Verzelen

This is a technical appendix to "Adaptive estimation of stationary Gaussian fields". We present several proofs that have been skipped in the main paper.

J. A. Diaz-Garcia, R. Gutierrez-Jaimez

In this paper, we extend the study of bivariate generalised beta type I and II distributions to the matrix variate case.

Rainer Dahlhaus

Correction to The Annals of Statistics (1989) 17 1749--1766 [URL: http://links.jstor.org/sici?sici=0090-5364%28198912%2917%3A4%3C1749%3AEPEFSP%3E 2.0.CO%3B2-9]