R_estep: Compute conditional covariance matrix for EM algorithms of...

Description Usage Arguments Value References See Also

View source: R/caoEtAl.R

Description

Computes conditional covariance of OD flows for E-step of EM algorithm from Cao et al. (2000) for their locally IID model.

Usage

1
R_estep(lambda, phi, A, c, epsilon)

Arguments

lambda

numeric vector (length k) of mean OD flows from last M-step

phi

numeric scalar scale for covariance matrix of xt

A

routing matrix (m x k) for network being analyzed

c

power parameter in model of Cao et al. (2000)

epsilon

numeric nugget to add to diagonal of covariance for numerical stability

Value

conditional covariance matrix (k x k) of OD flows given parameters

References

J. Cao, D. Davis, S. Van Der Viel, and B. Yu. Time-varying network tomography: router link data. Journal of the American Statistical Association, 95:1063-75, 2000.

See Also

Other CaoEtAl: Q_iid; Q_smoothed; grad_iid; grad_smoothed; locally_iid_EM; m_estep; phi_init; smoothed_EM


networkTomography documentation built on May 29, 2017, 4:56 p.m.