Perform numerical calculations for the ssden
and
sshzd
suites.
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)
Unpenalized terms evaluated at data points.
Basis of penalized terms evaluated at data points.
Penalty matrix.
Index of observations to be used as "knots."
Index of observations to be used as "knots."
Total number of lifetime observations.
Bin-counts for histogram data.
Unpenalized terms evaluated at quadrature nodes.
Basis of penalized terms evaluated at quadrature nodes.
Quadrature weights.
Precision requirement for internal iterations.
Maximum number of iterations allowed for internal iterations.
Parameter defining cross-validation score for smoothing parameter selection.
List of arrays incorporating possible sampling bias.
Flag indicating whether to use initial values of theta and skip theta iteration.
Integrals of basis terms.
Integrals of unpenalized terms.
Integrals of basis of penalized terms.
rho function value on failure times.
Weights at unique x.
Input for parametric random effects in nonparametric mixed-effect models.
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.
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.