mle_from_holq: Get MLE from output of 'holq'.
In tensr: Covariance Inference and Decompositions for Tensor Datasets

Description Usage Arguments Details Value Author(s) References See Also

From the output of holq, this function will calculate the MLEs for the component covariance matrices and for the total variation parameter.

1	mle_from_holq(holq_obj)

holq_obj

The output returned from holq.

The function simply takes the A[[i]] output of holq and returs A[[i]] %*% t(A[[i]]). The estimate of the total variation parameter is sqrt(sig ^ 2 / prod{p}), whre p is the vector of dimensions of the data array and sig is the output from holq.

cov_mle A list of positive definite matrices. These are the MLEs for the component covariance matrices.

sig_mle A numeric. This is an estimate of the "standard deviation" form of the total variation parameter.

David Gerard.

Gerard, D., & Hoff, P. (2016). A higher-order LQ decomposition for separable covariance models. Linear Algebra and its Applications, 505, 57-84. https://doi.org/10.1016/j.laa.2016.04.033 http://arxiv.org/pdf/1410.1094v1.pdf

holq.

tensr documentation built on May 2, 2019, 2:32 p.m.