drkpk {gss}R Documentation

Numerical Engine for ssden and sshzd

Description

Perform numerical calculations for the ssden and sshzd suites.

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. (2002), Smoothing Spline ANOVA Models. New York: Springer-Verlag.

Gu, C. and Wang, J. (2003), Penalized likelihood density estimation: Direct cross-validation and scalable approximation. Statistica Sinica, 13, 811–826.


[Package gss version 1.0-5 Index]