Linear Model Coefficient in Conditional Gaussian Models

DESCRIPTION:

Computes the linear model coefficients in conditional gaussian models.

USAGE:

cgmLmCoef(object, save = NULL, intercept = T) 

REQUIRED ARGUMENTS:

object
an object of class "missmodel" with a paramIter component that inherits from class "cgm".

OPTIONAL ARGUMENTS:

save
a vector giving the rows in the parameter matrix to be used in computing the linear model coefficients. If not specified, all rows in the paramIter matrix are used.
intercept
if TRUE, then it is assumed that the first coefficient in each linear model is equal to the intercept, and the intercept is translated to account for the initial standardization used on the continuous variables.

VALUE:

a array of dimension (r, p, n) containing the linear model coefficients, where r is the number of columns in the design matrix, p is the number of continuous variables in the model, and n is the length of save.

SEE ALSO:

, , , .

EXAMPLES:

stlouis.da3 <- daCgm(object = stlouis3[,-1], 
                     margins = ~risk:D1 + risk:D2 + D1:D2, 
                     design = ~D1*D2 + G, 
                     optData = data.frame(G = rep(-1:1, 4)), 
                     control = list(save = 101:5100, trace = T)) 
cgmLmCoef(object = stlouis.da3)