spaMM (version 2.4.35)

covStruct: Specifying correlation structures

Description

covStruct is a formal argument of HLCor, also handled by fitme and corrHLfit, that allows one to specify the correlation structure for different types of random effects, It is an alternative to other ad hoc formal arguments such as corrMatrix or adjMatrix. It is a list of matrices with names specifying the type of matrix considered: covStruct=list(corrMatrix=<some matrix>) or covStruct=list(adjMatrix=<some matrix>), where the “corrMatrix” or “adjMatrix” names are used to specify the type of information provided (accordingly, the names can be repeated: covStruct=list(corrMatrix=<.>,corrMatrix=<.>)). The covariance structure of a corrMatrix(1|<grouping factor>) formula term can be specified in two ways (see Examples): either by a correlation matrix factor (covStruct=list(corrMatrix=<some matrix>)), or by a precision matrix factor Q such that the covariance factor is \(\lambda\)Q\(^{-1}\), using the type name "precision": covStruct=list(precision=<some matrix>). In this case, an algorithm efficient for sparse precision matrices is used to fit the model.

Details

covStruct can also be specified as a list with an optional "types" attribute, e.g. structure(list(<some matrix>,types="corrMatrix"))

See Also

pedigree for a type of applications where declaring a precision matrix is useful.

Examples

# NOT RUN {
data("blackcap") 
# a 'dist' object can be used to specify a corrMatrix:  
MLdistMat <- MaternCorr(proxy::dist(blackcap[,c("latitude","longitude")]),
                        nu=0.6285603,rho=0.0544659) # a 'dist' object!
blackcap$name <- as.factor(rownames(blackcap))     
HLCor(migStatus ~ means + corrMatrix(1|name), data=blackcap,
      corrMatrix=MLdistMat, HLmethod="ML")
#### Same result by different input and algorithm:
m <- as.matrix(MLdistMat) ## leaves 0 on the diagonal! 
diag(m) <- 1 ## so that m is true correlation matrix 
prec_mat <- solve(m) ## precision factor matrix
HLCor(migStatus ~ means + corrMatrix(1|name), data=blackcap,
      covStruc=list(precision=prec_mat), HLmethod="ML")
# }