BackwardLinearRaff: Adapted Backward Algorithm for Partially Observed Data and...

In jordanaron22/PartiallyObservedHMM: HMM for Partiall Observed Three Diagnostic Test Data

Description

Adapted backward that incorporates partially observed data. Partial data is resolved in linear time. Also incorporates Rafferty Method as cited in paper. Assumes transition rate is the same when considering time t-1 and t-2 however allows for different weights (lambda)

Usage

BackwardLinearRaff(data, time, tran, class, lambda, max2, max3)

Arguments

data	two dimensional matrix for individual. 1st dimension is time 2nd is partially observed data
time	what time to caluclate for. Works recursivly, if time = t calculates for all values greater than t
tran	transition probabilities
class	classification probabilities
lambda	vector of length two, first value is weight given to value at time t-1, second value is weight given to value at time t-2
max2	number of values the second test can take on
max3	number of values the third test can take on

Value

list (each individual) of list (each time) of list (each partially observed data) of vector (forward probabilities)

jordanaron22/PartiallyObservedHMM documentation built on May 21, 2020, 6:49 p.m.