pyls.structures.PLSBootResults

class pyls.structures.PLSBootResults(**kwargs)

Dictionary-like object containing results of PLS bootstrap resampling

x_weights_normed

x_weights normalized by their standard error, obtained from bootstrap resampling (see x_weights_stderr)

Type

(B, L) numpy.ndarray

x_weights_stderr

Standard error of x_weights, used to generate x_weights_normed

Type

(B, L) numpy.ndarray

y_loadings

Covariance of features in Y with projected x_scores; not available with meancentered_pls()

Type

(J, L) numpy.ndarray

y_loadings_boot

Distribution of y_loadings across all bootstrap resamples; not available with meancentered_pls()

Type

(J, L, R) numpy.ndarray

y_loadings_ci

Lower (…, 0) and upper (…, 1) bounds of confidence interval for y_loadings; not available with meancentered_pls()

Type

(J, L, 2) numpy.ndarray

contrast

Group x condition averages of brainscores_demeaned. Can be treated as a contrast indicating group x condition differences. Only obtained from meancentered_pls.

Type

(J, L) numpy.ndarray

contrast_boot

Bootstrapped distribution of contrast; only available with meancentered_pls()

Type

(J, L, R) numpy.ndarray

contrast_ci

Lower (…, 0) and upper (…, 1) bounds of confidence interval for contrast; only available with meancentered_pls()

Type

(J, L, 2) numpy.ndarray

bootsamples

Indices of bootstrapped samples S across R resamples.

Type

(S, R) numpy.ndarray