Usage
move_step(y, X, tme, lambda, phi, lambdatm1, phitm1, prior, A, A1_inv, A2, rho, tau, m = ncol(X), l = nrow(A1_inv), k = length(lambda), ndraws = 10, minAccepts = 0, verbose = FALSE)
Arguments
y
numeric vector (length l) of observed link
loads
X
matrix (m x k) of particles for OD flows, one
particle per row, in pivoted order
tme
integer time index currently used in
estimation
lambda
matrix (m x k) of particles for OD
intensities, one particle per row, in pivoted order
phi
numeric vector (length m) of particles for
phi
lambdatm1
lambda matrix (m x k) of particles for
OD intensities from previous time, one particle per row,
in pivoted order
phitm1
numeric vector (length m) of particles for
phi from previous time
A
routing matrix (l x k) for network
A1_inv
inverse of full-rank portion of routing
matrix (l x l)
A2
remainder of routing matrix (l x k-l)
rho
numeric fixed autoregressive parameter for
dynamics on lambda; see reference for details
tau
numeric fixed power parameter for variance
structure on truncated normal noise; see reference for
details
m
integer number of particles
l
integer number of observed link loads
k
integer number of OD flows to infer
ndraws
integer number of draws to perform (can be
overriden by minAccepts)
minAccepts
integer minimum number of acceptances
before results are returned; activates alternative
stopping rule if >= 1
verbose
logical activates verbose diagnostic
output