qqchi {adehabitatLT} | R Documentation |

The functions allow the examination of the distribution of trajectories descriptors (see Details).

## Chi distribution of the increment length / sqrt(dt) qqchi(y, ...) ## Default S3 method: qqchi(y, df = 2, ylim, main = "Chi Q-Q Plot", xlab = "Theoretical Quantiles", ylab = "Sample Quantiles", plot.it = TRUE, datax = FALSE, ...) ## S3 method for class 'ltraj' qqchi(y, xlab = "Theoretical Quantiles", ylab = "Sample Quantiles (Distances)", ...) ## Normal Distribution of dx/sqrt(dt) or dy/sqrt(dt) ## S3 method for class 'ltraj' qqnorm(y, which=c("dx","dy"), ...)

`y` |
a vector containing the data sample for |

`df` |
the number of degrees of freedom of the Chi distribution (default to 2). |

`xlab, ylab, main` |
plot labels. |

`plot.it` |
logical. Should the result be plotted? |

`datax` |
logical. Should data values be on the x-axis? |

`which` |
a character string indicating the component (dx or dy) to be examined. |

`ylim, ...` |
graphical parameters. |

Among the numerous statistics that can be used to describe the
movements of an animal, the length of the increment between two
successive relocations is very common. This increment can be
described by a vector `i = c(dx, dy)`

. Under the hypothesis
of a Brownian motion, dx and dy should be normally distributed with
mean = 0 and variance = dt (where dt is the time interval between the
two relocations). Therefore, `dx/sqrt(dt)`

and
`dy/sqrt(dt)`

should be normally distributed with mean = 0 and
variance = 1. The function `qqnorm.ltraj`

performs a
quantile-quantile plot of `dx/sqrt(dt)`

or `dy/sqrt(dt)`

vs. a normal distribution to verify wether the Brownian motion
assumption is correct.

Furthermore, the quantity `(dx^2 + dy^2)/dt`

should be
distributed according to a Chi-squared distribution with two degrees
of freedom. Thus, the quantity `distance / sqrt(dt)`

should be
distributed according to a Chi distribution with two degrees of
freedom (where `distance`

is the distance between the two
relocations). The function `qqchi.ltraj`

performs
quantile-quantile plot of `distance/sqrt(dt)`

vs. a Chi
distribution to verify wether the Brownian motion
assumption is correct.

for functions dealing with objects of class `ltraj`

, a list with
components being themselves lists, with components:

`x` |
The x coordinates of the points that were/would be plotted |

`y` |
The original |

Clement Calenge clement.calenge@ofb.gouv.fr

## Example with an Arithmetic Brownian Process toto <- simm.mba(1:500, sig = diag(c(5, 5))) qqnorm(toto, "dx") qqnorm(toto, "dy") qqchi(toto) ## Example of wild boar data(puechcirc) qqnorm(puechcirc, "dx") qqnorm(puechcirc, "dy") qqchi(puechcirc)

[Package *adehabitatLT* version 0.3.25 Index]