6.1.2. statsmodels.sandbox.archive.linalg_decomp_1¶
Recipes for more efficient work with linalg using classes
intended for use for multivariate normal and linear regression calculations
x is the data (nobs, nvars) m is the moment matrix (x’x) or a covariance matrix Sigma
examples: x’sigma^{-1}x z = Px where P=Sigma^{-1/2} or P=Sigma^{1/2}
Initially assume positive definite, then add spectral cutoff and regularization of moment matrix, and extend to PCA
maybe extend to sparse if some examples work out (transformation matrix P for random effect and for toeplitz)
Author: josef-pktd Created on 2010-10-20
6.1.2.1. Functions¶
get_function_name(func) |
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maxabs(x) |
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testcompare(m1, m2) |
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tiny2zero(x[, eps]) |
replace abs values smaller than eps by zero, makes copy |
6.1.2.2. Classes¶
CholArray([data, sym]) |
Class that defines linalg operation on an array |
OneTimeProperty(func) |
A descriptor to make special properties that become normal attributes. |
PlainMatrixArray([data, sym]) |
Class that defines linalg operation on an array |
SvdArray([data, sym]) |
Class that defines linalg operation on an array |