drkpk {gss}R Documentation

Numerical Engine for ssden and sshzd

Description

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.

Usage

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)

Arguments

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.

Details

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.

References

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.


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