corgen {ecodist} R Documentation

## Generate correlated data

### Description

Generate correlated data of a given length.

### Usage

  corgen(len, x, r, population = FALSE, epsilon = 0)


### Arguments

 len Length of vectors. x Independent data. If x is specified, the population parameter is automatically set to TRUE. r Desired correlation between data vectors. population TRUE for vectors drawn from two populations with correlation r, otherwise r is the sample correlation. epsilon Desired tolerance.

### Details

Either x or len must be specified. If epsilon = 0, it has no effect, otherwise the sampling process is repeated until the sample correlation is within epsilon of r. This option allows the production of exactly-correlated data, within the limits of epsilon. Setting epsilon > 0 invalidates the population setting; data will be correlated within that range, rather than sampled from that population.If epsilon = 0, it has no effect, otherwise the sampling process is repeated until the sample correlation is within epsilon of r. This option allows the production of exactly-correlated data, within the limits of epsilon. Setting epsilon > 0 invalidates the population setting; data will be correlated within that range, rather than sampled from that population.If epsilon = 0, it has no effect, otherwise the sampling process is repeated until the sample correlation is within epsilon of r. This option allows the production of exactly-correlated data, within the limits of epsilon. Setting epsilon > 0 invalidates the population setting; data will be correlated within that range, rather than sampled from that population.

### Value

 x  First data vector, either generated by corgen or given by the user. y  Second data vector.

Sarah Goslee

### Examples


# create two random variables of length 100 with correlation
# of 0.10 +/- 0.01
xy <- corgen(len=100, r=.1, epsilon=0.01)
with(xy, cor(x, y))

# create two random variables of length 100 drawn from a population with
# a correlation of -0.82
xy <- corgen(len=100, r=-0.82, population=TRUE)
with(xy, cor(x, y))

# create a variable y within 0.01 of the given correlation to x
x <- 1:100
y <- corgen(x=x, r=.5, epsilon=.01)\$y
cor(x, y)


[Package ecodist version 2.0.9 Index]