mds: Fit distance sampling with movement model

In r-glennie/moveds: Fit Distance Sampling Models with Animal Movement

Description

Fit distance sampling with movement model

Usage

mds(ds, move, start, print = FALSE, level = 0.95, ...)

Arguments

ds	named list of distance sampling data: $data: matrix with observations for each row with (transect ID, x, y, t) columns $transect: matrix with transects for each row with (transect ID, length) $aux: vector of variables (region width, region length, truncation distance, observer speed, transect type 0line 1point) $delta: vector of discretisation sizes in (space, time) $hazardfn: code for hazard function to use (see ?hazardfns), default is 1 $move: 0 = 2d CDS model, 1 = 2d MDS model with estimated diffusion (must supply tag data), 2 = 2D MDS model with fixed diffusion (must supply fixed.sd)
move	named list of movement data: $fixed.sd fixed diffusion paramter, must be supplied and only used when ds$move = 2 $data list with matrix for each individual tagged with (x, y, t) observations in each row, required for ds$move = 1
start	named initial values for (detection scale, detection shape, diffusion rate (ds$move == 1))
print	FALSE by default, if TRUE then likelihood and parameters are printed after each evaluation
level	confidence interval level, default is 0.95
...	additional arguments to be passed to nlm (the optimisation routine)

Value

Named list: $result table of estimated parameters, standard errors, and confidence intervals $cor estimated correlation matrix between parameter estimates $penc average probability of detection $AIC Akaike's information criterion score for the model $fit the fitted model object output by optim $ds ds argument $move move argument $level confidence level supplied

r-glennie/moveds documentation built on Dec. 9, 2019, 9:42 p.m.