correct_positive_definite: Positive definite matrices

In LTFHPlus: Implementation of LT-FH++

Positive definite matrices

Description

correct_positive_definite verifies that a given covariance matrix is indeed positive definite by checking that all eigenvalues are positive. If the given covariance matrix is not positive definite, correct_positive_definite tries to modify the underlying correlation matrices genetic_corrmat and full_corrmat in order to obtain a positive definite covariance matrix.

Usage

correct_positive_definite(
  covmat,
  correction_val = 0.99,
  correction_limit = 100
)

Arguments

covmat	A symmetric and numeric matrix. If the covariance matrix should be corrected, it must have a number of attributes, such as attr(covmat,"fam_vec"), attr(covmat,"n_fam"), attr(covmat,"add_ind"), attr(covmat,"h2"), attr(covmat,"genetic_corrmat"), attr(covmat,"full_corrmat") and attr(covmat,"phenotype_names"). Any covariance matrix obtained by construct_covmat, construct_covmat_single or construct_covmat_multi will have these attributes by default.
correction_val	A positive number representing the amount by which genetic_corrmat and full_corrmat will be changed, if some eigenvalues are non-positive. That is, correction_val is the number that will be multiplied to all off_diagonal entries in genetic_corrmat and full_corrmat. Defaults to 0.99.
correction_limit	A positive integer representing the upper limit for the correction procedure. Defaults to 100.

Details

This function can be used to verify that a given covariance matrix is positive definite. It calculates all eigenvalues in order to investigate whether they are all positive. This property is necessary for the covariance matrix to be used as a Gaussian covariance matrix. It is especially useful to check whether any covariance matrix obtained by construct_covmat_multi is positive definite. If the given covariance matrix is not positive definite, correct_positive_definite tries to modify the underlying correlation matrices (called genetic_corrmat and full_corrmat in construct_covmat or construct_covmat_multi) by multiplying all off-diagonal entries in the correlation matrices by a given number.

Value

If covmat is a symmetric and numeric matrix and all eigenvalues are positive, correct_positive_definite simply returns covmat. If some eigenvalues are not positive and correction_val is a positive number, correct_positive_definite tries to convert covmat into a positive definite matrix. If covmat has attributes add_ind, h2, genetic_corrmat, full_corrmat and phenotype_names, correct_positive_definite computes a new covariance matrix using slightly modified correlation matrices genetic_corrmat and full_corrmat. If the correction is performed successfully, i.e. if the new covariance matrix is positive definite,the new covariance matrix is returned. Otherwise, correct_positive_definite returns the original covariance matrix.

See Also

construct_covmat, construct_covmat_single and construct_covmat_multi.

Examples

ntrait <- 2
genetic_corrmat <- matrix(0.6, ncol = ntrait, nrow = ntrait)
diag(genetic_corrmat) <- 1
full_corrmat <- matrix(-0.25, ncol = ntrait, nrow = ntrait)
diag(full_corrmat) <- 1
h2_vec <- rep(0.6, ntrait)
cov <- construct_covmat(fam_vec = c("m", "f"),
  genetic_corrmat = genetic_corrmat,
  h2 = h2_vec,
  full_corrmat = full_corrmat)
cov
correct_positive_definite(cov)

LTFHPlus documentation built on June 8, 2025, 11:47 a.m.