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In econometrics, the Park test is a test for heteroscedasticity. The test is based on the method proposed by Rolla Edward Park for estimating linear regression parameters in the presence of heteroscedastic error terms. ==Background== In regression analysis, ''heteroscedasticity'' refers to unequal variances of the random error terms εi, such that : var( ''ε''''i'' ) = E(( ''ε''''i'' )2 ) – (E (''ε''''i'' ) )2 = E(( ''ε''''i'' )2 ) = ( ''σ''''i'' )2. It is assumed that E(''ε''''i'') = 0. The above variance varies with ''i'', or the ''i''th trial in an experiment or the ''i''th case or observation in a dataset. Equivalently, heteroscedasticity refers to unequal conditional variances in the response variables ''Y''''i'', such that : var( ''Y''''i'' | ''X''''i'' ) = ( ''σ''''i'' )2, again a value that depends on ''i'' – or, more specifically, a value that is conditional on the values of one or more of the regressors ''X''. Homoscedasticity, one of the basic Gauss–Markov assumptions of ordinary least squares linear regression modeling, refers to equal variance in the random error terms regardless of the trial or observation, such that : var( ''ε''''i'' ) = ''σ''2, a constant. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Park test」の詳細全文を読む スポンサード リンク
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