drkpk: Numerical Engine for ssden, sshzd, and sshzd1

In gss: General Smoothing Splines

Numerical Engine for ssden, sshzd, and sshzd1

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, bias)
mspdsty(s, r, id.basis, cnt, qd.s, qd.r, qd.wt, prec, maxiter, alpha,
bias, skip.iter)

sspdsty1(s, r, q, cnt, int, prec, maxiter, alpha)
mspdsty1(s, r, id.basis, cnt, int, prec, maxiter, alpha)

mspcdsty(s, r, id.basis, cnt, qd.s, qd.r, xx.wt, qd.wt, prec, maxiter, alpha, skip.iter)

mspcdsty1(s, r, id.basis, cnt, int.s, int.r, prec, maxiter, alpha, skip.iter)

msphzd(s, r, id.wk, Nobs, cnt, qd.s, qd.r, qd.wt, random, prec, maxiter, alpha, skip.iter)

msphzd1(s, r, id.wk, Nobs, cnt, int.s, int.r, rho, random, prec, maxiter, alpha,
        skip.iter)

sspcox(s, r, q, cnt, qd.s, qd.r, qd.wt, prec, maxiter, alpha, random, bias)
mspcox(s, r, id.basis, cnt, qd.s, qd.r, qd.wt, prec, maxiter, alpha, random, bias,
       skip.iter)

mspllrm(s, r, id.basis, cnt, qd.s, qd.r, xx.wt, qd.wt, random, prec, maxiter, alpha,
        skip.iter)

Arguments

s	Unpenalized terms evaluated at data points.
r	Basis of penalized terms evaluated at data points.
q	Penalty matrix.
id.basis	Index of observations to be used as "knots."
id.wk	Index of observations to be used as "knots."
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.
bias	List of arrays incorporating possible sampling bias.
skip.iter	Flag indicating whether to use initial values of theta and skip theta iteration.
int	Integrals of basis terms.
int.s	Integrals of unpenalized terms.
int.r	Integrals of basis of penalized terms.
rho	rho function value on failure times.
xx.wt	Weights at unique x.
random	Input for parametric random effects in nonparametric mixed-effect models.

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

Du, P. and Gu, C. (2006), Penalized likelihood hazard estimation: efficient approximation and Bayesian confidence intervals. Statistics and Probability Letters, 76, 244–254.

Du, P. and Gu, C. (2009), Penalized Pseudo-Likelihood Hazard Estimation: A Fast Alternative to Penalized Likelihood. Journal of Statistical Planning and Inference, 139, 891–899.

Gu, C. (2013), Smoothing Spline ANOVA Models (2nd Ed). 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.

gss documentation built on Oct. 12, 2024, 1:08 a.m.