Q_smoothed: Q function for smoothed EM algorithm of Cao et al. (2000)

Description Usage Arguments Value References See Also

View source: R/caoEtAl.R

Description

Computes the Q function (expected log-likelihood) for the EM algorithm of Cao et al. (2000) for their smoothed model.

Usage

1
Q_smoothed(logtheta, c, M, rdiag, eta0, sigma0, V, eps.lambda, eps.phi)

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

eta0

numeric vector (length k+1) containing value for log(c(lambda, phi)) from previous time (or initial value)

sigma0

covariance matrix (k+1 x k+1) of log(c(lambda, phi)) from previous time (or initial value)

V

evolution covariance matrix (k+1 x k+1) for log(c(lambda, phi)) (random walk)

eps.lambda

numeric small positive value to add to lambda for numerical stability; typically 0

eps.phi

numeric small positive value to add to phi for numerical stability; typically 0

Value

numeric value of Q function; not vectorized in any way

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


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