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In this paper, we approach the variance changepoints detection problem from a multiple testing setting. After proving that the standard Step-Up and Step-Down procedures are inadmissible for the standa...
One may consider a discrete-event simulation as a Markov chain evolving on a suitably rich state space. One way that regenerative cycles may be constructed for general state-space Markov chains is to ...
Stein operators are differential operators which arise within the so-called Stein's method for stochastic approximation. We propose a new mechanism for constructing such operators for arbitrary (conti...
This article presents a functional Analysis of Variance model that explicitly incorporates phase variability through a time-warping component, allowing for a unified and parsimonious approach to estim...
The Brier Score is a widely-used criterion to assess the quality of probabilistic predictions of binary events. The expectation value of the Brier Score can be decomposed into the sum of three compone...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Non-stationarity of the event rate is a persistent problem in modeling time series of events, such as neuronal spike trains. Motivated by a variety of patterns in neurophysiological spike train record...
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic varia...
We study goodness-of-fit testing for non-causal autoregressive time series with non-Gaussian stable noise. To model time series exhibiting sharp spikes or occasional bursts of outlying observations, t...
Residual variance and the signal-to-noise ratio are important quantities in many statistical models and model fitting procedures. They play an important role in regression diagnostics, in determining ...
The problem of testing instantaneous causality between variables with time-varying unconditional variance is investigated. It is shown that the classi-cal tests based on the assumption of stationary p...
Classical analysis of variance requires that model terms be labeled as xed or random and typically culminate by comparing variability from each batch (factor) to variability from errors; without a st...
We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain.
In the game of Scrabble, letter tiles are drawn uniformly at random from a bag. The variability of possible draws as the game progresses is a source of variation that makes it more likely for an infer...
Let X be any absolutely continuous random variable from the integrated Pearson family and assume that X has finite moments of any order. Equivalently, X is a linear (non-constant) transformation of Y ...

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