derivQfun | R Documentation |
It computes the logQ function, its derivates of first and second order and the inverse of the hessian matrix for the SAEM estimated parameters.
derivQfun(est, fix.nugget = TRUE)
est |
object of the class "SAEMSpatialCens". See |
fix.nugget |
(logical) it indicates if the τ^2 parameter must be fixed. |
The logQ function refers to the logarithm of the Maximum likelihood conditional expectation, the first and second moments of the truncated normal distribution of censored data are involved in its computation.
Qlogvalue |
value of the logQ function evaluated in the SAEM estimates. |
gradQ |
gradient for the logQ function evaluated in the SAEM estimates. |
HQ |
hessian Matrix for the logQ function evaluated in the SAEM estimates. |
Qinv |
inverse of the negative Hessian matrix for the logQ function evaluated in the SAEM estimates. |
Alejandro Ordonez <<ordonezjosealejandro@gmail.com>>, Victor H. Lachos <<hlachos@ime.unicamp.br>> and Christian E. Galarza <<cgalarza88@gmail.com>>
Maintainer: Alejandro Ordonez <<ordonezjosealejandro@gmail.com>>
Diggle, P. & Ribeiro, P. (2007). Model-Based Geostatistics. Springer Series in Statistics.
Gradshtejn, I. S. & Ryzhik, I. M. (1965). Table of integrals, series and products. Academic Press.
SAEMSCL
require(geoR) data("Missouri") data=Missouri[1:70,] data$V3=log((data$V3)) cc=data$V5 y=data$V3 datare1=data coords=datare1[,1:2] data1=data.frame(coords,y) data1=data1[cc==0,] geodata=as.geodata(data1,y.col=3,coords.col=1:2) v=variog(geodata) v1=variofit(v) cov.ini=c(0,2) est=SAEMSCL(cc,y,cens.type="left",trend="cte",coords=coords,M=15,perc=0.25,MaxIter=5,pc=0.2, cov.model="exponential",fix.nugget=TRUE,nugget=2,inits.sigmae=cov.ini[2],inits.phi=cov.ini[1], search=TRUE,lower=0.00001,upper=50) d1=derivQfun(est) d1$QI
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