matlab linprog 多个自变量,科学网—多个自变量，如何确定哪个更重要? - 梅卫平的博文...

最新推荐文章于 2025-04-01 12:22:23 发布

转载最新推荐文章于 2025-04-01 12:22:23 发布 · 392 阅读

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#matlab linprog 多个自变量

该内容涉及回归分析中的R^2分解，包括Details、pmvdist、last、first、betasq、pratt、genizi和car等多个度量。这些度量用于评估各变量在回归模型中的贡献，如变量的边际方差分解、标准化系数和加权平均贡献等。此外，还提到了Feldman(2005)和Zuber与Strimmer(2010)的研究成果。

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Details

lmg

is the R^2 contribution averaged over orderings among regressors, cf. e.g. Lindeman, Merenda and Gold 1980, p.119ff or Chevan and Sutherland (1991).

pmvd

is the proportional marginal variance decomposition as proposed by Feldman (2005) (non-US version only). It can be interpreted as a weighted average over orderings among regressors, with data-dependent weights.

last

is each variables contribution when included last, also sometimes called "usefulness".

first

is each variables contribution when included first, which is just the squared covariance between y and the variable.

betasq

is the squared standardized coefficient.

pratt

is the product of the standardized coefficient and the correlation.

genizi

is the R^2 decomposition according to Genizi 1993

car

is the R^2 decomposition according to Zuber and Strimmer 2010, also available from package care (squares of scores produced by function carscore