28 citations · 30 across the 7 of their papers we have counts for
7 papers
Stationary Proportional Hazard Processes via Complementary Power Function Distribution Processes
Barry C. Arnold, B. G. Manjunath, S. Sachdeva
In the following, we introduce new proportional hazard (PH) processes, which are derived by a marginal transformation applied to complementary power function distribution (CPFD) pr…
Goodness of fit tests for the pseudo-Poisson distribution
Banoth Veeranna, B. G. Manjunath, B. Shobha
Bivariate count models having one marginal and the other conditionals being of the Poissons form are called pseudo-Poisson distributions. Such models have simple exible dependence…
Some power function distribution processes
Barry C. Arnold, Sachin Sachdeva, B. G. Manjunath
It is known that all the proportional reversed hazard (PRH) processes can be de?rived by a marginal transformation applied to a power function distribution (PFD) process. Kundu [8]…
Bivariate distributions with equi-dispersed normal conditionals and related models
Barry C. Arnold, B. G. Manjunath
A random variable is equi-dispersed if its mean equals its variance. A Poisson distribution is a classical example of this phenomenon. However, a less well-known fact is that the c…
Statistical Inference for distributions with one Poisson conditional
Barry C. Arnold, B. G. Manjunath
It will be recalled that the classical bivariate normal distributions have normal marginals and normal conditionals. It is natural to ask whether a similar phenomenon can be encoun…
Moments Calculation For the Doubly Truncated Multivariate Normal Density
Manjunath B G, Stefan Wilhelm
In the present article we derive an explicit expression for the trun- cated mean and variance for the multivariate normal distribution with ar- bitrary rectangular double truncatio…
A note on gaussian distributions in R^n
B. G. Manjunath, K. R. Parthasarathy
Given any finite set F of (n - 1)-dimensional subspaces of R^n we give examples of nongaussian probability measures in R^n whose marginal distribution in each subspace from F is ga…