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emulate.ctmm

Draw a random model-fit from the sampling distribution


Description

This function generates random model-fit statistics from the sampling distribution of a given ctmm movement model and sampling schedule. If fast=FALSE, the results are exact, though slow to evaluate. Else if fast=TRUE, the central-limit theorem is invoked.

Usage

emulate(object,...)

## S3 method for class 'ctmm'
emulate(object,data=NULL,fast=FALSE,...)

## S3 method for class 'telemetry'
emulate(object,CTMM,fast=FALSE,...)

Arguments

object

telemetry data or ctmm model object.

CTMM

A ctmm movement-model object.

data

Optional telemetry object for exact results.

fast

Whether or not to invoke the central-limit theorem.

...

Arguments passed to ctmm.fit.

Details

Given fast=FALSE, which requires the data argument specified, new data are simulated from the CTMM movement model with the same sampling schedule and error structure as data. A new model, of the same structure as CTMM, is then fit to the simulated data and returned.

Given fast=TRUE, a model-fit object is sampled from the central-limit distribution, using the covariance estimates within CTMM. Strictly positive parametes, such as area, are log-transformed prior to the normal approximation. Note that this faster method does not adjust for bias.

Value

A ctmm movement model with the same structure as CTMM.

Author(s)

C. H. Fleming.

See Also


ctmm

Continuous-Time Movement Modeling

v0.6.0
GPL-3
Authors
Christen H. Fleming [aut, cre], Justin M. Calabrese [aut], Xianghui Dong [ctb], Kevin Winner [ctb], Guillaume Péron [ctb], Michael J. Noonan [ctb], Bart Kranstauber [ctb], Eliezer Gurarie [ctb], Kamran Safi [ctb], Paul C. Cross [dtc], Thomas Mueller [dtc], Rogério C. de Paula [dtc], Thomas Akre [dtc], Jonathan Drescher-Lehman [dtc], Autumn-Lynn Harrison [dtc], Ronaldo G. Morato [dtc]
Initial release
2021-01-08

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