Compute least squares estimates and IVX estimates with pairwise quantile predictive regressions (R package)
-
Updated
Aug 9, 2023 - R
Compute least squares estimates and IVX estimates with pairwise quantile predictive regressions (R package)
Calculate the covariance of two single-precision floating-point strided arrays provided known means and using a one-pass textbook algorithm.
Compute the covariance of two one-dimensional single-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm.
Compute the covariance matrix for an `M` by `N` double-precision floating-point matrix `A` and assigns the results to a matrix `B` when provided known means and using a one-pass textbook algorithm.
Calculate the covariance of two double-precision floating-point strided arrays provided known means and using a one-pass textbook algorithm.
Calculate the covariance of two strided arrays provided known means and using a one-pass textbook algorithm.
Compute the covariance of two one-dimensional ndarrays provided known means and using a one-pass textbook algorithm.
Compute the covariance of two one-dimensional double-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm.
Add a description, image, and links to the covar topic page so that developers can more easily learn about it.
To associate your repository with the covar topic, visit your repo's landing page and select "manage topics."