heteroscedastic
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Robust regression — In robust statistics, robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non parametric methods. Regression analysis seeks to find the effect of one or more independent… … Wikipedia
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Linear discriminant analysis — (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The… … Wikipedia
Homoscedasticity — Plot with random data showing homoscedasticity. In statistics, a sequence or a vector of random variables is homoscedastic ( … Wikipedia
Heteroscedasticity — In statistics, a sequence or a vector of random variables is heteroskedastic, or heteroscedastic, if the random variables have different variances. The complementary concept is called homoskedasticity. The term means differing variance and comes… … Wikipedia
MINQUE — In statistics, the theory of minimum norm quadratic unbiased estimation (MINQUE)[1][2][3] was developed by C.R. Rao. Its application was originally to the estimation of variance components in random effects models. The theory involves three… … Wikipedia
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Behrens–Fisher problem — In statistics, the Behrens–Fisher problem is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed… … Wikipedia
heteroscedasticity — noun The property of a series of random variables of not every variable having the same finite variance Ant: homoscedasticity See Also: heteroscedastic … Wiktionary
Dummy variable (statistics) — In statistics and econometrics, particularly in regression analysis, a dummy variable (also known as an indicator variable) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to … Wikipedia