Results 21 to 30 of about 213,571 (250)
Goodness of fit for stochastic actor-oriented models
We propose a Mahalanobis distance–based Monte Carlo goodness of fit testing procedure for the family of stochastic actor-oriented models for social network evolution.
Josh Lospinoso, Tom AB Snijders
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Efficient algorithm for testing goodness-of-fit for classification of high dimensional data
Let us have a sample satisfying d-dimensional Gaussian mixture model (d is supposed to be large). The problem of classification of the sample is considered. Because of large dimension it is natural to project the sample to k-dimensional (k = 1, 2, . . .)
Gintautas Jakimauskas
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Goodness-of-Fit Test for the Bivariate Hermite Distribution
This paper studies the goodness of fit test for the bivariate Hermite distribution. Specifically, we propose and study a Cramér–von Mises-type test based on the empirical probability generation function. The bootstrap can be used to consistently estimate
Pablo González-Albornoz +1 more
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Some Goodness of Fit Tests for Random Sequences
In this paper we had made an attempt to incorporate the results from the theory of square Gaussian random variables in order to construct the goodness of fits test for random sequences (time series). We considered two versions of such tests.
Yuriy Kozachenko, Tetiana Ianevych
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Multivariate goodness-of-fit tests based on kernel density estimators
The paper is devoted to multivariate goodness-of-fit ests based on kernel density estimators. Both simple and composite null hypotheses are investigated.
Aleksej Bakshaev, Rimantas Rudzkis
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A Novel Goodness-of-Fit Test for Cauchy Distribution
Recently, several goodness-of-fit tests for Cauchy distribution have been introduced based on Kullback–Leibler divergence and likelihood ratio. It is claimed that these tests are more powerful than the well-known goodness-of-fit tests such as Kolmogorov ...
A. Pekgör
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Goodness–of–Fit Tests for Bivariate Time Series of Counts
This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being
Šárka Hudecová +2 more
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Goodness of fit by Neyman-Pearson testing
The Neyman-Pearson strategy for hypothesis testing can be employed for goodness of fit if the alternative hypothesis is selected from data by exploring a rich parametrised family of models, while controlling the impact of statistical fluctuations.
Gaia Grosso, Marco Letizia, Maurizio Pierini, Andrea Wulzer
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Testing Goodness-of-Fit of Parametric Spatial Trends
The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametric trend surface, that is, a regression model with spatially correlated errors.
Andrea Meilán-Vila +3 more
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We develop a new type of generative autoencoder called the Goodness-of-Fit Autoencoder (GoFAE), which incorporates GoF tests at two levels. At the minibatch level, it uses GoF test statistics as regularization objectives. At a more global level, it selects a regularization coefficient based on higher criticism, i.e., a test on the uniformity of the ...
Aaron Palmer +3 more
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