PST (version 0.94.1)

logLik: Log-Likelihood of a variable length Markov chain model

Description

Retrieve the log-likelihood of a fitted VLMC. This is the logLik method for objects of class PSTf returned by the pstree and prune functions.

Usage

# S4 method for PSTf
logLik(object)

Value

An object of class logLik, a negative numeric value with the df (degrees of freedom) attribute containing the number of free parameters of the model.

Arguments

object

a probabilistic suffix tree, i.e., an object of class "PSTf" as returned by the pstree, prune or tune function.

Author

Alexis Gabadinho

Details

The likelihood of a learning sample containing \(n\) sequences, given a model \(S\) fitted to it, is $$ L(S)=\prod_{i=1}^{n} P^{S}(x^{i}) $$ where \(P^{S}(x^{i})\) is the probability of the \(i\)th observed sequence predicted by \(S\). Note that the log-likelihood of a VLMC model is not used in the estimation of the model's parameters (see pstree). It is obtained once the model is estimated by calling the predict function. The value is stored in the logLik slot of the probabilistic suffix tree representing the model (a PSTf object returned by the pstree or prune function). The AIC and BIC values can also be obtained with the corresponding generic functions, which call logLik and use its result. For more details, see Gabadinho 2016.

References

Gabadinho, A. & Ritschard, G. (2016). Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package. Journal of Statistical Software, 72(3), pp. 1-39.

See Also

AIC, BIC

Examples

## activity calendar for year 2000
## from the Swiss Household Panel
## see ?actcal
data(actcal)

## selecting individuals aged 20 to 59
actcal <- actcal[actcal$age00>=20 & actcal$age00 <60,]

## defining a sequence object
actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
actcal.seq <- seqdef(actcal,13:24,labels=actcal.lab)

## building a PST
actcal.pst <- pstree(actcal.seq, nmin=2, ymin=0.001)
logLik(actcal.pst)

## Cut-offs for 5% and 1% (see ?prune)
C99 <- qchisq(0.99,4-1)/2

## pruning
actcal.pst.C99 <- prune(actcal.pst, gain="G2", C=C99)

## Comparing AIC
AIC(actcal.pst, actcal.pst.C99)