In this work, we propose a novel procedure for deriving a discrete counterpart to a continuous probability distribution. This procedure or, better, this class of procedures, is based on an appropriate distance between cumulative distribution functions. A discrete random distribution, supported on the set of integer values, is obtained by minimizing its distance to the assigned continuous probability distribution. An application is provided with reference to the negative exponential distribution, along with a comparison with an existing discretization technique
In the present work, we consider discretization of continuous distributions and study relations bet...
Practical computational limits for stochastic decision analysis models often require that probabilit...
We propose a new discrete distribution namely the discrete weighted exponential (dWE) distribution. ...
In this work, we propose a novel procedure for deriving a discrete counterpart to a continuous proba...
We consider the problem of approximating a continuous random variable, characterized by a cumulative...
In many real-world applications, the random variables modeling the phenomena of interest are continu...
Modeling correlated count data through some bivariate (or multivariate) discrete distribution is ess...
While discretization of continuous distributions have been attempted for many life distributions the...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
This paper is concerned with distances for comparing multivariate random vectors with a special focu...
Abstract. Continuous probability distributions are widely used to mathematically describe random phe...
The paper obtains a discrete analogue of the normal distribution as the distribution that is charact...
Discrete analogue of a continuous distribution (especially in the univariate domain) is not new in t...
The Kolmogorov distance is used to transform arithmetic severities into equispaced arithmetic severi...
Master's thesis is focused on solution of the statistical problem to find a probability distribution...
In the present work, we consider discretization of continuous distributions and study relations bet...
Practical computational limits for stochastic decision analysis models often require that probabilit...
We propose a new discrete distribution namely the discrete weighted exponential (dWE) distribution. ...
In this work, we propose a novel procedure for deriving a discrete counterpart to a continuous proba...
We consider the problem of approximating a continuous random variable, characterized by a cumulative...
In many real-world applications, the random variables modeling the phenomena of interest are continu...
Modeling correlated count data through some bivariate (or multivariate) discrete distribution is ess...
While discretization of continuous distributions have been attempted for many life distributions the...
In order to carry out the simulation, we need a source of random numbers distributed according to th...
This paper is concerned with distances for comparing multivariate random vectors with a special focu...
Abstract. Continuous probability distributions are widely used to mathematically describe random phe...
The paper obtains a discrete analogue of the normal distribution as the distribution that is charact...
Discrete analogue of a continuous distribution (especially in the univariate domain) is not new in t...
The Kolmogorov distance is used to transform arithmetic severities into equispaced arithmetic severi...
Master's thesis is focused on solution of the statistical problem to find a probability distribution...
In the present work, we consider discretization of continuous distributions and study relations bet...
Practical computational limits for stochastic decision analysis models often require that probabilit...
We propose a new discrete distribution namely the discrete weighted exponential (dWE) distribution. ...