poissonProb: Compute predictive probabilities based on Poisson

In ocp: Bayesian Online Changepoint Detection

Description

Compute the probability of observing the current point, given the current parameters of the poisson for each possible run length. Returns a vector of predictive probabilities from each possible run length, the parameters of the poisson, the most likely lambda of the current poisson, and the current point.

Usage

poissonProb(update_params0, update_paramsT, datapt, time, cps, missPts,
  Rlength, skippt = FALSE)

Arguments

update_params0	The initialization parameters, corresponding to predicting a changepoint (run length=0)
update_paramsT	The vectors of parameters corresponding to each possible run length, updated with each incoming data point
datapt	the current data point
time	the number of time points passed so far
cps	the current most likely list of changepoints
missPts	the method set to handle missing points
Rlength	the length of the current vector of possible run lengths
skippt	If the current point should be skipped in the updating because it was missing, and missPts was set to skip

Value

Returns a vector of predictive probabilities from each possible run length, the parameters of the gaussian, the most likely mean of the current gaussian, and the current point.

ocp documentation built on May 2, 2019, 3:46 a.m.