relativeRate {ADMUR} | R Documentation |

## Calculates the relative growth (or decline) rate per generation.

### Description

Calculates the generational growth/decline rate for a linear piece of a CPL model, or between any two x,y coordinate pairs.

### Usage

`relativeRate(x, y, generation = 25, N = 1000)`

### Arguments

`x` |
A numeric vector of length 2, giving the start and end date of linear piece, or a 2 column matrix such that each row is a start and end pair. |

`y` |
The corresponding y values such as PDs, or population size (numeric vector of length 2), or a matrix such that each row is a start and end pair. |

`generation` |
Years per generation. Default = 25. |

`N` |
Number of sections to average the growth rate across. |

### Details

The 'relative rate' (growth or decline) of a straight line between two x,y coordinate pairs is the expected generational growth rate across this line. It is calculated always relative to the larger y-value, providing a symmetric measure. E.g., the absolute percentage changes from 80 to 100 to 80 are calculated as +20 The expected rate is the mean average of the conventional rates for N equal sections of the line, as N approaches infinity.

### Value

Returns a numeric vector of values between 0 and 100 representing a 'relative percentage rate per generation'. Negative values indicate a decline through time, positive indicate growth.

### Examples

```
x <- c(5600,5500)
y <- c(75,80)
# conventional growth/decline rate per 25 yr generation
100 * exp(log(y[2]/y[1])/((x[1]-x[2])/25)) - 100
# relative growth/decline rate per 25 yr generation
relativeRate(x,y)
x <- c(5600,5500)
y <- c(480,75)
# conventional growth/decline rate per 25 yr generation
100 * exp(log(y[2]/y[1])/((x[1]-x[2])/25)) - 100
# relative growth/decline rate per 25 yr generation
relativeRate(x,y)
x <- c(5600,5500)
y <- c(480,0)
# conventional growth/decline rate per 25 yr generation
100 * exp(log(y[2]/y[1])/((x[1]-x[2])/25)) - 100
# relative growth/decline rate per 25 yr generation
relativeRate(x,y)
# various random rates between 6000 and 5500 BP
x <- t(matrix(c(6000,5500),2,1000))
y <- matrix(runif(2000),1000,2)
conventional <- 100 * exp(log(y[,2]/y[,1])/((x[,1]-x[,2])/25)) - 100
relative <- relativeRate(x,y)
plot(relative, conventional)
```

*ADMUR*version 1.0.3 Index]