Estimation methods

Estimating equations

In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments, least squares, and maximum likelihood—as well as some recent methods like M-estimators. The basis of the method is to have, or to find, a set of simultaneous equations involving both the sample data and the unknown model parameters which are to be solved in order to define the estimates of the parameters. Various components of the equations are defined in terms of the set of observed data on which the estimates are to be based. Important examples of estimating equations are the likelihood equations. (Wikipedia).

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From playlist Differential Equations: Complete Set of Course Videos

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From playlist Introduction to Linear Equations in One Variable

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Related pages

Estimation | Method of moments (statistics) | Consistent estimator | Median | M-estimator | Generalized estimating equation | Probability density function | Sample mean | Statistical model | Exponential distribution | Least squares | Generalized method of moments