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  2. Coefficient of multiple correlation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_multiple...

    In statistics, the coefficient of multiple correlation is a measure of how well a given variable can be predicted using a linear function of a set of other variables. It is the correlation between the variable's values and the best predictions that can be computed linearly from the predictive variables. [1]

  3. Generalized additive model for location, scale and shape

    en.wikipedia.org/wiki/Generalized_additive_model...

    The generalized additive model for location, scale and shape (GAMLSS) is a semiparametric regression model in which a parametric statistical distribution is assumed for the response (target) variable but the parameters of this distribution can vary according to explanatory variables.

  4. Uncertainty coefficient - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_coefficient

    In statistics, the uncertainty coefficient, also called proficiency, entropy coefficient or Theil's U, is a measure of nominal association. It was first introduced by Henri Theil [citation needed] and is based on the concept of information entropy.

  5. Measurement uncertainty - Wikipedia

    en.wikipedia.org/wiki/Measurement_uncertainty

    In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale.. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.

  6. Generalized estimating equation - Wikipedia

    en.wikipedia.org/wiki/Generalized_estimating...

    In statistics, a generalized estimating equation (GEE) is used to estimate the parameters of a generalized linear model with a possible unmeasured correlation between observations from different timepoints.

  7. Robust regression - Wikipedia

    en.wikipedia.org/wiki/Robust_regression

    The analysis was performed in R using software made available by Venables and Ripley (2002). The two regression lines appear to be very similar (and this is not unusual in a data set of this size). However, the advantage of the robust approach comes to light when the estimates of residual scale are considered.

  8. Minimum-variance unbiased estimator - Wikipedia

    en.wikipedia.org/wiki/Minimum-variance_unbiased...

    In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.

  9. Phi coefficient - Wikipedia

    en.wikipedia.org/wiki/Phi_coefficient

    In statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or r φ) is a measure of association for two binary variables.. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.