get_cov_mat: Calculate a covariance matrix
In mlondschien/hdcd: High - Dimensional Change Point Detection

Calculate a covariance matrix of the design matrix x using one of the methods complete_observations, pairwise_covariance, loh_wainwright_bias_correction or average_imputation.

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get_cov_mat(x, NA_method = c("complete_observations",
  "pairwise_covariance", "loh_wainwright_bias_correction",
  "average_imputation"), min_points = 2)

`x`	A n x p design matrix
`NA_method`	The method that should be applied to estimate the covariance structure.
`min_points`	Minimal number of available observations of a variable necessary such that an estimation of the variance of that variable is reliable. An integer not smaller than 2.

A p x p matrix with an estimate for the covariance structure of x. If less than min_points observations are available for some variable, the corresponding rows and columns are NA.

mlondschien/hdcd documentation built on Jan. 5, 2021, 11:26 p.m.