grad_iid: Compute analytic gradient of Q-function for locally IID EM...

Description Usage Arguments Value References See Also

View source: R/caoEtAl.R

Description

Computes gradient of Q-function with respect to log(c(lambda,phi)) for EM algorithm from Cao et al. (2000) for their locally IID model.

Usage

1
grad_iid(logtheta, c, M, rdiag, epsilon)

Arguments

logtheta

numeric vector (length k+1) of log(lambda) (1:k) and log(phi) (last entry)

c

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

M

matrix (n x k) of conditional expectations for OD flows, one time per row

rdiag

numeric vector (length k) containing diagonal of conditional covariance matrix R

epsilon

numeric nugget to add to diagonal of covariance for numerical stability

Value

numeric vector of same length as logtheta containing calculated gradient

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; R_estep; grad_smoothed; locally_iid_EM; m_estep; phi_init; smoothed_EM


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