This is an internal function of package
calculates the inner product of a matrix (from a Kronecker product)
and a sparse weight matrix in order to obtain standard errors. It
uses the same idea employed in
MortSmooth.BWB and the elements
after the IWLS converged, including the penalty term.
Mort2Dsmooth_se(RTBx, RTBy, nbx, nby, BWB.P1)
tensors product of B-splines basis for the x-axis.
tensors product of B-splines basis for the y-axis.
number of B-splines for the x-axis.
number of B-splines for the y-axis.
inverse of the LHS of the Poisson system of equations.
This function is only used within
when standard errors are required. The arguments
BWB.P1 is the
LHS after convergence is reached and smoothing parameter selected. The
standard errors as given in the function are computed for the linear
predictor term and simple computation is needed to obtain standard
errors for the Poisson counts. Anyway
predict.Mort2Dsmooth takes care of such differences.
The Generalized Linear Array Models setting is explained in the
A matrix of standard errors for the linear predictor term.
Carlo G Camarda
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