km {asbio} | R Documentation |
Kaplan-Meier survivorship.
Description
Calculates survivorship for individuals in a population over time based on the method of Kaplan-Meier; cf. Pollock et al. (1989).
Usage
km(r, d, var = "O", conf = 0.95, age.seq=seq(1,length(r)),
ylab = "Survivorship", xlab = "Age class", type = "b",
plot.km = TRUE, plot.CI = TRUE, ...)
Arguments
r |
Numbers of individuals at risk in each age or time class. |
d |
Vector of the number of deaths in each age or time class. |
var |
Type of procedure used to calculate variance in confidence intervals |
conf |
Level of confidence for confidence interval calculations; 1 - P(type I error) |
age.seq |
A sequence of numbers indicating the age classes used. |
ylab |
Y-axis label. |
xlab |
X-axis label. |
type |
|
plot.km |
Logical. Should plot be created? |
plot.CI |
Logical. Should confidence interval be overlaid on plot? |
... |
Additional arguments from |
Details
Details for this index are given in Pollock et al. (1989).
Value
Returns a list with the following components
s.hat |
A vector of estimated survivorship probabilities from the 1st age class onward. |
Greenwood.Var |
The estimated Greenwood variance for each age class. |
Oakes.Var |
The estimated Oakes variance for each age class. |
CI |
Upper and lower confidence bound to the true survivorship. |
Author(s)
Ken Aho
References
Pollock, K. H., Winterstein, S. R., and Curtis, P. D. (1989) Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management. 53(1):7-1.
Examples
##Example from Pollock (1989)
r<-c(18,18,18,16,16,16,15,15,13,10,8,8,7)
d<-c(0,0,2,0,0,1,0,1,1,1,0,0,0)
km(r,d)