oldlogspline density, distribution function, hazard
function or survival function
from
a logspline density that was fitted using
the 1992 knot deletion algorithm.
The 1997 algorithm using knot
deletion and addition is available using the logspline function.plot.oldlogspline(x, n = 100, what = "d", xlim, xlab = "", ylab = "",
type = "l", ...)logspline object, typically the result of logspline."d" (density), "p" (distribution function), "s" (survival
function) or "h" (hazard function).oldlogspline fit at n equally
spaced points roughly covering the support of the density. (Use
xlim=c(from,to) to change the range of these points.)Charles J. Stone, Mark Hansen, Charles Kooperberg, and Young K. Truong. The use of polynomial splines and their tensor products in extended linear modeling (with discussion) (1997). Annals of Statistics, 25, 1371--1470.
logspline,
oldlogspline,
summary.oldlogspline,
doldlogspline,
poldlogspline,
qoldlogspline,
roldlogspline.y <- rnorm(100)
fit <- oldlogspline(y)
plot(fit)Run the code above in your browser using DataLab