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 `"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`.

### 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.

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)
```

[Package asbio version 1.7 Index]