A method that combines the maximum likelihood and the method of moments for estimating the parameters of the K distribution is proposed. The method results in the lowest variance of parameter estimates when compared with existing non-ML techniques
We present a computational approach to the method of moments using Monte Carlo simulation. Simple al...
Moments and cumulants are commonly used to characterize the probability distribution or ob-served da...
A procedure for estimating the effectiveness of algorithms which retrieve size distribution paramete...
A method that combines the maximum likelihood and the method of moments for estimating the parameter...
We propose a method for estimating the parameters of the K- distribution on a manner which significa...
of the bachelor's thesis Title: Parameter estimation of random variables distribution Author: Bc. Ba...
Binomial distribution of order k , geometric distribution of order k , Poisson distribution of order...
The two statistical principles of maximum entropy and maximum likelihood are investigated for the th...
This report consists of three parts, the first one dealing with the unbiased, minimum-variance estim...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
It is often necessary to find a Weibull distribution with specified mean, variance, and location par...
Moments and cumulants are commonly used to characterize the probability distribution or observed dat...
Fitting distributions to data has a long history and many different procedures have been advocated. ...
The K-distribution is an important probability distribution to describe radar reflectivity of clutte...
Estimation of parameter in a new discrete distribution which is analogous to Burr distribution is di...
We present a computational approach to the method of moments using Monte Carlo simulation. Simple al...
Moments and cumulants are commonly used to characterize the probability distribution or ob-served da...
A procedure for estimating the effectiveness of algorithms which retrieve size distribution paramete...
A method that combines the maximum likelihood and the method of moments for estimating the parameter...
We propose a method for estimating the parameters of the K- distribution on a manner which significa...
of the bachelor's thesis Title: Parameter estimation of random variables distribution Author: Bc. Ba...
Binomial distribution of order k , geometric distribution of order k , Poisson distribution of order...
The two statistical principles of maximum entropy and maximum likelihood are investigated for the th...
This report consists of three parts, the first one dealing with the unbiased, minimum-variance estim...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
It is often necessary to find a Weibull distribution with specified mean, variance, and location par...
Moments and cumulants are commonly used to characterize the probability distribution or observed dat...
Fitting distributions to data has a long history and many different procedures have been advocated. ...
The K-distribution is an important probability distribution to describe radar reflectivity of clutte...
Estimation of parameter in a new discrete distribution which is analogous to Burr distribution is di...
We present a computational approach to the method of moments using Monte Carlo simulation. Simple al...
Moments and cumulants are commonly used to characterize the probability distribution or ob-served da...
A procedure for estimating the effectiveness of algorithms which retrieve size distribution paramete...
DOI
Add to ORKG