Results 71 to 80 of about 123 (118)

Shape mixtures of multivariate skew-normal distributions

Classes of shape mixtures of independent and dependent multivariate skew-normal distributions are considered and some of their main properties are studied.
Loschi, Rosangela H., Genton, Marc G., Arellano-Valle, Reinaldo B.   +2 more
core  

Diagonal distribution of a complex non-central Wishart matrix: A new trivariate non-central chi-squared density

This paper derives the joint density of a particular trivariate non-central [chi]2 distribution corresponding to the diagonal elements of a 3x3 complex non-central Wishart matrix.
McKay, Matthew R., Dharmawansa, Prathapasinghe   +1 more
core  

Generalizations of Runs and Patterns Distributions for Sequences of Binary Trials. [PDF]

Methodol Comput Appl Probab, 2021
Dafnis SD, Makri FS, Koutras MV.
europepmc   +1 more source

Zero-inflated beta distribution applied to word frequency and lexical dispersion in corpus linguistics. [PDF]

J Appl Stat, 2020
Burch B, Egbert J.
europepmc   +1 more source

Copula-based measures of asymmetry between the lower and upper tail probabilities. [PDF]

Stat Pap (Berl), 2022
Kato S, Yoshiba T, Eguchi S.
europepmc   +1 more source

A New Regression Model for the Analysis of Overdispersed and Zero-Modified Count Data. [PDF]

Entropy (Basel), 2021
Bertoli W, Conceição KS, Andrade MG, Louzada F.   +3 more
europepmc   +1 more source

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
core  

A bivariate inverse Weibull distribution and its application in complementary risks model. [PDF]

J Appl Stat, 2020
Mondal S, Kundu D.
europepmc   +1 more source

Joint distributions of numbers of occurrences of a discrete pattern and weak convergence of an empirical process for the pattern

For a {0, 1}-pattern of finite length, an empirical process is introduced in order to describe the number of overlapping occurrences of the pattern at each level t[set membership, variant][0,1] in a sequence of the corresponding indicators of i.i.d.
Aki, Sigeo
core  

The Variance-Gamma Product Distribution. [PDF]

Results Math
Gaunt RE, Li S, Sutcliffe HL.
europepmc   +1 more source