km: 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, ...)

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.

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 "O" = Oakes, "G" = Greenwood.
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: type argument from plot.
plot.km: Logical. Should plot be created?
plot.CI: Logical. Should confidence interval be overlaid on plot?
...: Additional arguments from plot.

Author

Ken Aho

Details

Details for this index are given in Pollock et al. (1989).

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

Run this code

##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)

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