View source: R/MultiLambdaCVfun.R
mgcv_lambda | R Documentation |
Computed maximum marginal likelihood score for given penalty parameters using mgcv
.
mgcv_lambda(penalties, XXblocks,Y, model=NULL, printscore=TRUE, pairing=NULL, sigmasq = 1, opt.sigma=ifelse(model=="linear",TRUE, FALSE))
penalties |
Numeric vector. |
XXblocks |
List of |
Y |
Response vector: numeric, binary, factor or |
model |
Character. Any of |
printscore |
Boolean. Should the score be printed? |
pairing |
Numerical vector of length 3 or |
sigmasq |
Default error variance. |
opt.sigma |
Boolean. Should the error variance be optimized as well? Only relevant for |
See gam
for details on how the marginal likelihood is computed.
Numeric, marginal likelihood score for given penalties
Wood, S. N. (2011), Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models, J. Roy. Statist. Soc., B 73(1), 3-36.
CVscore
for cross-validation alternative. A full demo and data are available from:
https://drive.google.com/open?id=1NUfeOtN8-KZ8A2HZzveG506nBwgW64e4
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