Description Usage Arguments Value Author(s) References Examples
This function returns the negative log-likelihood of the specified mixture model.
1 | mxtrmodLL(params, obsY, xVars, zVars, Tvals, includeDiscrete)
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params |
A vector of parameter estimates for all paramters in the mixture model. |
obsY |
A vector containing the response variable, which must be normally or log normally distributed. If lognormal, log transformed Y's should be input as the response variable. Missing Y values should be indicated by NA. |
xVars |
The design matrix for the covariates included in the discrete portion of the model. |
zVars |
The design matrix for the covariates inlcuded in the continuous portion of the model. |
Tvals |
A vector of thresholds below which continuous variables are not observable. |
includeDiscrete |
A logical indicator for whether or not to include the discrete portion of the model. |
Returns the negative log-likelihood of the specified mixture model.
Michael Nodzenski, Anna Reisetter, Denise Scholtens
Moulton LH, Halsey NA. A mixture model with detection limits for regression analyses of antibody response to vaccine. Biometrics. 1995 Dec;51(4):1570-8.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | #Create sample data
set.seed(123)
yvar<-rlnorm(200)
these<-sample(1:100,20)
yvar[these]<-NA
logyvar<-log(yvar)
y2var<-rlnorm(200)
those<-sample(1:200,25)
y2var[those]<-NA
logy2var<-log(y2var)
pred1<-sample(0:1,200,replace=TRUE)
pred2<-sample(1:10,200,replace=TRUE)
testdata<-data.frame(cbind(yvar,y2var,logyvar,logy2var,pred1,pred2))
#Create a vector of starting values for the function
startvals<-c(2,0,0,1.5,0,0,2)
#Create a vector of response variables
obsY<-testdata$logyvar
#Create the design matrix for the discrete portion of the model
xVars<-model.matrix(~pred1+pred2,data=testdata)
#Create the design matrix for the continuous portion of the model
zVars<-model.matrix(~pred1+pred2,data=testdata)
#Create the Tvals vector
Tvals<-rep(min(obsY,na.rm=TRUE),length(obsY))
#Determine if the discrete portion should be inlcuded in the model
includeDiscrete<-sum(is.na(obsY))>5
#Calculate the negative log-likelihood
mxtrmodLL(params=startvals,obsY=obsY,xVars=xVars,zVars=zVars,Tvals=Tvals,
includeDiscrete=includeDiscrete)
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