- Econometrics
- >
- Estimation theory
- >
- Estimation methods
- >
- Probability distribution fitting

- Measures (measure theory)
- >
- Probability distributions
- >
- Theory of probability distributions
- >
- Probability distribution fitting

- Probability theory
- >
- Probability distributions
- >
- Theory of probability distributions
- >
- Probability distribution fitting

- Sample statistics
- >
- Summary statistics
- >
- Frequency distribution
- >
- Probability distribution fitting

- Statistical inference
- >
- Estimation theory
- >
- Estimation methods
- >
- Probability distribution fitting

- Statistical models
- >
- Probability distributions
- >
- Theory of probability distributions
- >
- Probability distribution fitting

- Statistical theory
- >
- Probability distributions
- >
- Theory of probability distributions
- >
- Probability distribution fitting

- Statistics
- >
- Statistical methods
- >
- Estimation methods
- >
- 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

Overdispersion

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 .

© 2023 Useful Links.