mortality.calculation {CTFS} | R Documentation

## Compute Annual Mortality Rates and Confidence Limits given N, S and Time

### Description

A simple function to calculate mortality and confidence limits from N0 (number alive at the outset), S (number of survivors), and time (time interval). Values can be vectors or scalars.

### Usage

    mortality.calculation(N0, S, meantimeint)

### Arguments

`N0` | number of trees at the first census
`S` | number of trees that survived to the second census, N - D
`meantimeint` | interval between censuses in years for trees in the first census

### Details

This function is called many times by `mortality`. It can be used directly but it is primarily intended as an internal function. `N0, S` and `meantimeint` can be single values or vectors. For full details on computation of mortality rate and confidence limits see `CTFS.mortality`.

### Value

`mortality.calculation` returns a dataframe with the following components:

`N0` | number of trees at the first census
`S` | number of trees that survived to the second census, N - D
`D` | number of dead trees
`rate` | annual mortality rate
`lowerCI` | lower 95% confidence interval
`upperCI` | upper 95% confidence interval
`meantimeint` | mean number of years between intervals

### Author(s)

Rick Condit, Pamela Hall

### See Also

`CTFS.mortality`

### Examples

    ## Not run:
    # 1. Default use of mortality.calculation()

    mortality.calculation(500, 490, 5)

    # N0   S  D        rate     lowerCI     upperCI meantimeint
    # 1 500 490 10 0.004040541 0.002214243 0.007415848           5

    # 2. Input values as vectors
    N0 = c(100, 100, 100)
    S = c(90, 80, 70)
    time = c(5, 5, 5)
    mortality.calculation(N0,S,time)

    # N0  S  D       rate    lowerCI    upperCI meantimeint
    # 1 100 90 10 0.02107210 0.01144898 0.03836600           5
    # 2 100 80 20 0.04462871 0.02867126 0.06825114           5
    # 3 100 70 30 0.07133499 0.04943058 0.10088494           5
    ## End(Not run)

[Package CTFS version 1.00 Index]