Statistical Applications of the Multivariate Skew Normal Distribution [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1999 Summary Azzalini and Dalla Valle have recently discussed the multivariate skew normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further probabilistic properties of the distribution, with special emphasis on aspects of statistical ...
AZZALINI, ADELCHI, CAPITANIO A.
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Some Statistical Aspects of the Truncated Multivariate Skew-t Distribution
Mathematics, 2022 The multivariate skew-t distribution plays an important role in statistics since it combines skewness with heavy tails, a very common feature in real-world data.
Raúl Alejandro Morán-Vásquez +2 more
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On the Multivariate Asymptotic Distribution of Sequential Chi-Square Statistics
Psychometrika, 1985 The multivariate asymptotic distribution of sequential Chi-square test statistics is investigated. It is shown that: (a) when sequential Chi-square statistics are calculated for nested models on the same data, the statistics have an asymptotic intercorrelation which may be expressed in closed form, and which is, in many cases, quite high; and (b ...
Steiger, James H. +2 more
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Asymptotic distribution of rank statistics under dependencies with multivariate application
Journal of Multivariate Analysis, 1990 [X\({}_ n=(X_{1n},...,X_{Jn}),1\leq n\leq N]\) is a set of independent random vectors of length J, the marginal cdfs being absolutely continuous. Define \(u(x)=1\) or 0 according to whether \(x\geq 0\) or \(x\), \(=\), or \(
G. L. Thompson
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On the distributions of a class of statistics in multivariate analysis
Journal of Multivariate Analysis, 1972 AbstractThe noncentral distributions of Y = Πi=1p θia(1 − θi)b are obtained, where a and b are known real numbers and θi's stand for latent roots of a matrix arising in each of three situations in multivariate normal theory, namely, test of equality of two covariance matrices, MANOVA, and canonical correlation. The study is extended to the complex case
Pillai, K.C.S, Nagarsenker, B.N
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Distribution-on-distribution regression with Wasserstein metric: Multivariate Gaussian case [PDF]
Journal of Multivariate Analysis, 2023 Distribution data refers to a data set where each sample is represented as a probability distribution, a subject area receiving burgeoning interest in the field of statistics.
Ryotaro Okano, M. Imaizumi
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Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference [PDF]
Journal of Computational And Graphical Statistics, 2021 In this article, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions.
Luiza S. C. Piancastelli +3 more
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Choosing Among Notions of Multivariate Depth Statistics [PDF]
Statistical Science, 2020 Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance from the mean, which is based on the mean and the covariance matrix of the data.
K. Mosler, Pavlo Mozharovskyi
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Plithogenic Probability & Statistics are generalizations of MultiVariate Probability & Statistics [PDF]
Neutrosophic Sets and Systems, 2021 In this paper we exemplify the types of Plithogenic Probability and respectively Plithogenic Statistics. Several applications are given. The Plithogenic Probability of an event to occur is composed from the chances that the event occurs with respect to ...
Florentin Smarandache
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Wavelet Based Multivariate Signal Denoising Using Mahalanobis Distance and EDF Statistics [PDF]
IEEE Transactions on Signal Processing, 2020 A multivariate signal denoising method is proposed which employs a novel multivariate goodness of fit (GoF) test that is applied at multiple data scales obtained from discrete wavelet transform (DWT).
K. Naveed, N. Rehman
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