logp: logp

In mmppr: Markov Modulated Poisson Process for Unsupervised Event Detection in Time Series of Counts

Description

Estimates the marginal likelihood of the data using the samples

Usage

logp(N, samples, priors, iter, EQUIV)

Arguments

N	Matrix of count data; axis 0 is the number of time intervals per day and axis 1 is the number of days in the data.
samples	List of different samples at all time periods
priors	List with parameter values of prior distributions
iter	Number of iterations over which to calcuate likelihood.
EQUIV	Parameter sharing controls <- c(S1, S2): S1 <- force sharing of delta (day effect) among days, S2 <- force sharing of eta (time of day) among days, Values: 1 (all days share), 2 (weekdays/weekends), 3 (none)

mmppr documentation built on May 2, 2019, 4:18 a.m.