indmove {adehabitatLT} | R Documentation |

The function `indmove`

tests for the independence between
successive components `c(dx, dy)`

for each burst in a regular
object of class `ltraj`

.

The function `indmove.detail`

tests for the independence between
successive `dx`

or `dy`

for each burst in a regular object
of class `ltraj`

.

The function `testang.ltraj`

tests for the independence between
successive angles (relative or absolute) for each burst in a regular
object of class `ltraj`

.

The function `testdist.ltraj`

tests for the independence between
successive distances between successive relocations for each burst in
a regular object of class `ltraj`

.

indmove(ltr, nrep = 200, conflim = seq(0.95, 0.5, length=5), sep = ltr[[1]]$dt[1], units = c("seconds", "minutes", "hours", "days"), plotit = TRUE) testang.ltraj(x, which = c("absolute", "relative"), nrep = 999, alter = c("two-sided","less","greater")) testdist.ltraj(x, nrep = 999, alter = c("two-sided","less","greater")) indmove.detail(x, detail=c("dx","dy"), nrep=999, alter = c("two-sided","less","greater"))

`ltr,x` |
an object of class |

`conflim` |
a vector giving the limits of the confidence intervals to be plotted |

`nrep` |
number of simulations |

`units` |
a character string indicating the time units for the result |

`alter` |
a character string specifying the alternative hypothesis, must be one of "greater", "less" or "two-sided" (default) |

`which` |
a character string indicating whether the absolute or relative angles are under focus |

`detail` |
a character string indicating whether |

`plotit` |
logical. Whether the results should be plotted on a graph |

`sep` |
used in the case of variable time lag between relocations. Indicates the theoretical time lag between two relocations |

The function `indmove`

randomises the order of the increments
`c(dx, dy)`

in a trajectory. The criteria of the test is the
Mean Squared Displacement (`R^2_n`

) (Root & Kareiva 1984).

The function `testang.ltraj`

randomises the order of the angles in a
trajectory. The criteria of the test is ```
f^2 = sum_(i=1)^(n-1) 2*(1 -
cos(angle[i+1] - angle[i]))
```

. This measure corresponds to the
mean squared length of the segment joining two successive angles on
the trigonometric circle (see examples for an illustration).

The function `testdist.ltraj`

randomises the order of the
distances between successive relocations in a trajectory. The
criteria of the test is ```
sum_(i=1)^(n-1) (dist[i+1] -
dist[i])^2
```

(Neuman 1941, Neuman et al. 1941). The same criteria is
used in `indmove.detail()`

.

Note that these functions require "regular" trajectories, i.e. trajectories for which the relocations are separated by a constant time lag.

Finally, note that the functions `testang.ltraj`

and
`testdist.ltraj`

are not affected by the presence of missing
values in the bursts of relocations. The function `indmove`

may
be greatly affected by these missing values (they are removed prior to
the test).

`indmove()`

returns a list with one component per burst. Each
component is a list of two data frames. The data frame `Time`

contains the time points at which R2n is computed for the
observation (first column) and the simulations (other ones). The data
frame `R2n`

contains the values for the R2n (same dimensions).

`testang.ltraj()`

, `testdist.ltraj`

and
`indmove.detail`

return lists of
objects of class `randtest`

.

Clement Calenge clement.calenge@ofb.gouv.fr

Stephane Dray dray@biomserv.univ-lyon1.fr

Root, R.B. & Kareiva, P.M. (1984) The search for resources by
cabbage butterflies (Pieris Rapae): Ecological consequences and
adaptive significance of markovian movements in a patchy
environment. *Ecology*, **65**: 147–165.

Neumann, J.V., Kent, R.H., Bellinson, H.R. & Hart, B.I. (1941) The mean
square successive difference. *Annals of Mathematical
Statistics*, **12**: 153–162.

Neumann, J.V. (1941) Distribution of the ration of the mean square
successive difference to the variance. *The Annals of
Mathematical Statistics*, **12**: 367–395.

## Not run: ## theoretical independence between br <- simm.brown(1:1000) testang.ltraj(br) testdist.ltraj(br) indmove(br) ## End(Not run) ## Illustration of the statistic used for the test of the independence ## of the angles opar <- par(mar = c(0,0,4,0)) plot(0,0, asp=1, xlim=c(-1, 1), ylim=c(-1, 1), ty="n", axes=FALSE, main="Criteria f for the measure of independence between successive angles at time i-1 and i") box() symbols(0,0,circle=1, inches=FALSE, lwd=2, add=TRUE) abline(h=0, v=0) x <- c( cos(pi/3), cos(pi/2 + pi/4)) y <- c( sin(pi/3), sin(pi/2 + pi/4)) arrows(c(0,0), c(0,0), x, y) lines(x,y, lwd=2, col="red") text(0, 0.9, expression(f^2 == 2*sum((1 - cos(alpha[i]-alpha[i-1])), i==1, n-1)), col="red") foo <- function(t, alpha) { xa <- sapply(seq(0, alpha, length=20), function(x) t*cos(x)) ya <- sapply(seq(0, alpha, length=20), function(x) t*sin(x)) lines(xa, ya) } foo(0.3, pi/3) foo(0.1, pi/2 + pi/4) foo(0.11, pi/2 + pi/4) text(0.34,0.18,expression(alpha[i]), cex=1.5) text(0.15,0.11,expression(alpha[i-1]), cex=1.5) par(opar)

[Package *adehabitatLT* version 0.3.25 Index]