drkpk {gss} | R Documentation |
Calculate penalized likelihood density estimates and hazard
estimates via the Newton iteration and evaluate the cross-validation
score, as implemented in the RATFOR routine dnewton.r
and
hzdnewton.r
, and minimize the cross-validation score using
nlm
and nlm0
.
sspdsty(s,r,q,cnt,qd.s,qd.r,qd.wt,prec,maxiter,alpha) mspdsty(s,r,q,cnt,qd.s,qd.r,qd.wt,prec,maxiter,alpha) msphzd(s,r,q,Nobs,cnt,qd.s,qd.r,qd.wt,prec,maxiter,alpha)
s |
Unpenalized terms evaluated at data points. |
r |
Basis of penalized terms evaluated at data points. |
q |
Penalty matrix. |
Nobs |
Total number of lifetime observations. |
cnt |
Bin-counts for histogram data. |
qd.s |
Unpenalized terms evaluated at quadrature nodes. |
qd.r |
Basis of penalized terms evaluated at quadrature nodes. |
qd.wt |
Quadrature weights. |
prec |
Precision requirement for internal iterations. |
maxiter |
Maximum number of iterations allowed for internal iterations. |
alpha |
Parameter defining cross-validation score for smoothing parameter selection. |
sspdsty
is used by ssden
to compute
cross-validated density estimate with a single smoothing
parameter. mspdsty
is used by ssden
to compute
cross-validated density estimate with multiple smoothing
parameters.
msphzd
is used by sshzd
to compute
cross-validated hazard estimate with single or multiple smoothing
parameters.
Gu, C. and Wang, J. (2002), Penalized Likelihood Density Estimation: Direct Cross-Validation and Scalable Approximation. Available at stat.purdue.edu/~chong/manu.html.
Gu, C. (2002), Smoothing Spline ANOVA Models. New York: Springer-Verlag.