Minimum-distance estimation (MDE) is a conceptual method for fitting a statistical model to data, usually the empirical distribution. Often-used estimators...

The term minimum distance may refer to Minimum distance estimation, a statistical method for fitting a model to data Closest pair of points problem, the...

+X_{iT}\lambda _{T}+e_{i}+u_{it}} which can be estimated by minimum distance estimation. Need to have more than one time-variant regressor ( X {\displaystyle...

of support, a variation of the maximum likelihood technique Minimum-distance estimation Partial likelihood methods for panel data Quasi-maximum likelihood...

distributions, it can be used in parameter estimation as the basis for a form of minimum distance estimation procedure. The test is named after Theodore...

conditions, and can therefore be thought of as a special case of minimum-distance estimation. The GMM estimators are known to be consistent, asymptotically...

distributions. It is also used as a part of other algorithms, such as minimum distance estimation. It is defined as ω 2 = ∫ − ∞ ∞ [ F n ( x ) − F ∗ ( x ) ] 2 d...

Pafnuty Chebyshev. It is also known as chessboard distance, since in the game of chess the minimum number of moves needed by a king to go from one square...

to that sample. The MISE is also known as L2 risk function. Minimum distance estimation Mean squared error Wand, M. P.; Jones, M. C. (1994). Kernel smoothing...

{\displaystyle D_{\text{KL}}(P\parallel Q)} , is a type of statistical distance: a measure of how one reference probability distribution P is different...