| dhare {polspline} | R Documentation |
Density (dhare), cumulative probability (phare), hazard rate (hhare), quantiles
(qhare), and random samples (rhare) from
a hare object.
dhare(q, cov, fit) hhare(q, cov, fit) phare(q, cov, fit) qhare(p, cov, fit) rhare(n, cov, fit)
q |
vector of quantiles. Missing values (NAs) are allowed. |
p |
vector of probabilities. Missing values (NAs) are allowed. |
n |
sample size. If length(n) is larger than 1, then
length(n) random values are returned.
|
cov |
covariates. There are several possibilities. If a vector of length
fit\$ncov is provided, these covariates are used for all elements of p or
q or for all random numbers. If a matrix of dimension length(p),
length(q), or n by fit\$ncov is provided, the rows of cov are
matched with the elements of p or q or every row of cov has its own
random number. If a matrix of dimension m times fit\$ncov is provided,
while length(p) = 1 or length(q) = 1 or n = 1, the single element of p or q is
used m times, or m random numbers with different sets of covariates are
generated.
|
fit |
hare object, typically obtained from hare. |
Elements of q or p that are missing will cause the
corresponding elements of the result to be missing.
Densities (dhare), hazard rates (hhare),
probabilities (phare), quantiles (qhare),
or a random sample (rhare) from a hare object.
Charles Kooperberg clk@fhcrc.org.
Charles Kooperberg, Charles J. Stone and Young K. Truong (1995). Hazard regression. Journal of the American Statistical Association, 90, 78-94.
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.
hare,
plot.hare,
summary.hare.
fit <- hare(testhare[,1], testhare[,2], testhare[,3:8]) dhare(0:10, testhare[117,3:8], fit) hhare(0:10, testhare[1:11,3:8], fit) phare(10, testhare[1:25,3:8], fit) qhare((1:19)/20, testhare[117,3:8], fit) rhare(10, testhare[117,3:8], fit)