anisotropic.fit | R Documentation |
Fits SECR model using distances calculated in a space transformed by compression along a single axis. Both the orientation of the axis (ψ_A) and the compression ratio (ψ_R) are treated as parameters to be estimated. The general method was first applied by Murphy et al. (2016).
anisotropic.fit(..., psiA = pi/4, psiR = 2) predictAniso(fit, angle = c("degrees", "radians"))
... |
arguments passed to ] |
psiA |
numeric initial value of phiA |
psiR |
numeric initial value of phiR |
fit |
fitted model from |
angle |
units for angle |
The compression ratio ψ_R takes values greater than or equal to 1.0. The corresponding coefficient on the link scale is log(ψ_R - 1).
The function predictAniso
extracts estimates of the transformation parameters from a fitted model and back-transforms psiR.
The estimate of the spatial scale parameter sigma applies in the isotropic compressed space; it may be understood as an estimate along the minor axis of each ellipse.
For anisotropic.fit
, a fitted secr model.
For predictAniso
, a dataframe of two rows (psiA, psiR).
Murphy, S. M., Cox, J. J., Augustine, B. C., Hast, J. T., Guthrie, J. M., Wright, J., McDermott, J., Maehr, S. C. and Plaxico, J. H. (2016) Characterizing recolonization by a reintroduced bear population using genetic spatial capture–recapture. Journal of Wildlife Management 80, 1390–1407.
secr.fit
## view the function used internally for distances secrBVN:::anisodistfn ## simulate data tr <- make.grid(10, 10, spacing = 25, hollow = TRUE, detector = 'proximity') pop <- simpopn.bvn(s2xy = (25*c(0.5,2))^2, theta = pi/4, core = tr, buffer = 200, D = 4, Ndist = 'fixed') CH <- simcapt.bvn(tr, pop, type = 'BVN', lambda = 0.4, noccasions = 5) ## fit model fit <- anisotropic.fit(CH, buffer = 200, detectfn = 'HHN', trace = FALSE) ## examine results coef(fit) predictAniso(fit) predict(fit)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.