Wishartness and independence of matrix quadratic forms in a normal random matrix
Let Y be an nxp multivariate normal random matrix with general covariance [Sigma]Y. The general covariance [Sigma]Y of Y means that the collection of all np elements in Y has an arbitrary npxnp covariance matrix. A set of general, succinct and verifiable
Hu, Jianhua
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Copula-based measures of asymmetry between the lower and upper tail probabilities. [PDF]
Stat Pap (Berl), 2022 Kato S, Yoshiba T, Eguchi S.
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Zero-inflated beta distribution applied to word frequency and lexical dispersion in corpus linguistics. [PDF]
J Appl Stat, 2020 Burch B, Egbert J.
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A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data. [PDF]
Entropy (Basel), 2021 Bertoli W +3 more
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Bivariate generalized exponential distribution
Recently it has been observed that the generalized exponential distribution can be used quite effectively to analyze lifetime data in one dimension. The main aim of this paper is to define a bivariate generalized exponential distribution so that the ...
Kundu, Debasis, Gupta, Rameshwar D.
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A bivariate inverse Weibull distribution and its application in complementary risks model. [PDF]
J Appl Stat, 2020 Mondal S, Kundu D.
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A class of bivariate exponential distributions
We introduce a class of absolutely continuous bivariate exponential distributions, generated from quadratic forms of standard multivariate normal variates.
Regoli, Giuliana
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On Stein's lemma, dependent covariates and functional monotonicity in multi-dimensional modeling
Tracking the correct directions of monotonicity in multi-dimensional modeling plays an important role in interpreting functional associations. In the presence of multiple predictors, we provide empirical evidence that the observed monotone directions via
Li, Jialiang +2 more
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The Variance-Gamma Product Distribution. [PDF]
Results MathGaunt RE, Li S, Sutcliffe HL.
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Canonical representation of conditionally specified multivariate discrete distributions
Most work on conditionally specified distributions has focused on approaches that operate on the probability space, and the constraints on the probability space often make the study of their properties challenging.
Wang, Yuchung J., Ip, Edward H.
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