Category: Probability distribution fitting

Maximum spacing estimation
In statistics, maximum spacing estimation (MSE or MSP), or maximum product of spacing estimation (MPS), is a method for estimating the parameters of a univariate statistical model. The method requires
Partial likelihood methods for panel data
Partial (pooled) likelihood estimation for panel data is a quasi-maximum likelihood method for panel analysis that assumes that density of yit given xit is correctly specified for each time period but
Maximum likelihood estimation
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihoo
Method of moments (statistics)
In statistics, the method of moments is a method of estimation of population parameters. The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the pop
In statistics, overdispersion is the presence of greater variability (statistical dispersion) in a data set than would be expected based on a given statistical model. A common task in applied statisti
Probability distribution fitting
Probability distribution fitting or simply distribution fitting is the fitting of a probability distribution to a series of data concerning the repeated measurement of a variable phenomenon.The aim of
Empirical likelihood
Empirical likelihood (EL) is a nonparametric method that requires fewer assumptions about the error distribution while retaining some of the merits in likelihood-based inference. The estimation method
Testing in binary response index models
Denote a binary response index model as: , where .