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pro vyhledávání: '"62H15"'
Autor:
Kager, Wouter, Meester, Ronald
We investigate the asymptotic relation between likelihood ratios and p-values. We do that in a setting in which exact computations are possible: a coin-tossing context where the hypotheses of interest address the success probability of the coin. We o
Externí odkaz:
http://arxiv.org/abs/2408.12905
In the statistical literature, as well as in artificial intelligence and machine learning, measures of discrepancy between two probability distributions are largely used to develop measures of goodness-of-fit. We concentrate on quadratic distances, w
Externí odkaz:
http://arxiv.org/abs/2407.16374
Autor:
Guella, Jean Carlo
In this paper, we characterize several classes of continuous radial basis functions that can be employed to determine whether a interaction of a probability is zero or not. These functions encompass standard independence tests but also the Lancaster/
Externí odkaz:
http://arxiv.org/abs/2407.06854
In this article, we introduce the novel concept of the second maximum of a Gaussian random field on a Riemannian submanifold. This second maximum serves as a powerful tool for characterizing the distribution of the maximum. By utilizing an ad-hoc Kac
Externí odkaz:
http://arxiv.org/abs/2406.18397
Autor:
Lukić, Žikica
In this paper, we present a novel test for determining equality in distribution of matrix distributions. Our approach is based on the integral squared difference of the empirical Laplace transforms with respect to the noncentral Wishart measure. We c
Externí odkaz:
http://arxiv.org/abs/2406.10733
Autor:
Dörnemann, Nina, Paul, Debashis
In this paper, the key objects of interest are the sequential covariance matrices $\mathbf{S}_{n,t}$ and their largest eigenvalues. Here, the matrix $\mathbf{S}_{n,t}$ is computed as the empirical covariance associated with observations $\{\mathbf{x}
Externí odkaz:
http://arxiv.org/abs/2404.19176
Autor:
Díaz, Mateo, Chandrasekaran, Venkat
Controlling the false discovery rate (FDR) is a popular approach to multiple testing, variable selection, and related problems of simultaneous inference. In many contemporary applications, models are not specified by discrete variables, which necessi
Externí odkaz:
http://arxiv.org/abs/2404.09142
Asymptotic methods for hypothesis testing in high-dimensional data usually require the dimension of the observations to increase to infinity, often with an additional condition on its rate of increase compared to the sample size. On the other hand, m
Externí odkaz:
http://arxiv.org/abs/2403.16328
Testing the equality of mean vectors across $g$ different groups plays an important role in many scientific fields. In regular frameworks, likelihood-based statistics under the normality assumption offer a general solution to this task. However, the
Externí odkaz:
http://arxiv.org/abs/2403.07679
Spherical and hyperspherical data are commonly encountered in diverse applied research domains, underscoring the vital task of assessing independence within such data structures. In this context, we investigate the properties of test statistics relyi
Externí odkaz:
http://arxiv.org/abs/2401.11540