Add to ORKGThree new distributions are derived for sums of independent truncated Poisson variates, namely, the generalized Stirling, the R, and the D distributions. They depend respectively on the generalized Stirling, R, and D numbers which are defined, studied, and tabulated. Recursion, decomposition, and recurrence relations, limiting and modal properties of these new distributions and numbers are investigated. The moments are obtained. MVU estimators of the probability functions (p.f.\u27s) of these distributions and computational methods for these numbers and p.f.\u27s are also given. In addition, the D distribution is extended to the D compound distribution when the number of truncated Poisson variables to be summed is considered as a random var...
We derive upper bounds for the total variation distance, d, between the distributions of two random ...
This paper presents new Gaussian approximations for the cumulative distri-bution function P(Aλ ≤ s) ...
The random variable X taking values 0,1,2,…,x,… with probabilities pλ(x) = e−λλx/x!, where λ∈R0+ is ...
<p>A new distribution (the v-Poisson) and its conjugate density are introduced and explored using co...
In this paper we give a recursive scheme, involving Panjer's recursion, to compute the distribu...
ABSTRACT. In this article we survey properties of mixed Poisson distributions and probabilistic aspe...
Within the theory of non-negative integer valued multivariate infinitely divisible distributions, th...
In these paper we introduce a new class of exponential sums from which various known as well as new ...
In this paper, we construct a new Lagrangian discrete distribution, named the Lagrangian zero trunca...
Let X be a random variable having a Poisson distributionand mean . Using the unified generalizations...
Motivated mainly by lifetime issues, a new lifetime distribution coined ``Discrete Poisson-Gold dist...
Given a sample from a discrete compound Poisson distribution, we consider variants of plug-in and li...
Note: Missing Page 118.In 1837 a paper by Poisson [61] was published in France, establishing the Poi...
After providing a systematic outline of the stochastic genesis of the Poisson–Tweedie distribution, ...
summary:The compound Poisson-gamma variable is the sum of a random sample from a gamma distribution ...
We derive upper bounds for the total variation distance, d, between the distributions of two random ...
This paper presents new Gaussian approximations for the cumulative distri-bution function P(Aλ ≤ s) ...
The random variable X taking values 0,1,2,…,x,… with probabilities pλ(x) = e−λλx/x!, where λ∈R0+ is ...
<p>A new distribution (the v-Poisson) and its conjugate density are introduced and explored using co...
In this paper we give a recursive scheme, involving Panjer's recursion, to compute the distribu...
ABSTRACT. In this article we survey properties of mixed Poisson distributions and probabilistic aspe...
Within the theory of non-negative integer valued multivariate infinitely divisible distributions, th...
In these paper we introduce a new class of exponential sums from which various known as well as new ...
In this paper, we construct a new Lagrangian discrete distribution, named the Lagrangian zero trunca...
Let X be a random variable having a Poisson distributionand mean . Using the unified generalizations...
Motivated mainly by lifetime issues, a new lifetime distribution coined ``Discrete Poisson-Gold dist...
Given a sample from a discrete compound Poisson distribution, we consider variants of plug-in and li...
Note: Missing Page 118.In 1837 a paper by Poisson [61] was published in France, establishing the Poi...
After providing a systematic outline of the stochastic genesis of the Poisson–Tweedie distribution, ...
summary:The compound Poisson-gamma variable is the sum of a random sample from a gamma distribution ...
We derive upper bounds for the total variation distance, d, between the distributions of two random ...
This paper presents new Gaussian approximations for the cumulative distri-bution function P(Aλ ≤ s) ...
The random variable X taking values 0,1,2,…,x,… with probabilities pλ(x) = e−λλx/x!, where λ∈R0+ is ...