boutsMLEll: Log likelihood function of parameters given observed data

In diveMove: Dive Analysis and Calibration

Log likelihood function of parameters given observed data

Description

This function defines a closure, where x will be the object passed to it.

Usage

boutsMLEll.chooser(x, x0, transformed = TRUE)

.bouts2MLEll(x, p, lambda0, lambda1)

.bouts3MLEll(x, p0, p1, lambda0, lambda1, lambda2)

Arguments

x	numeric vector of independent data to be described by the function.
x0	numerical one-dimensional vector of coefficients.
transformed	logical indicating whether coefficients need to be transformed back to original scale to compute the negative log likelihood.
p, lambda0, lambda1	numeric: parameters of the model.
p0, p1, lambda2	numeric: parameters of the model.

Value

ll.chooser returns the negative log likelihood function of the joint distribution.

numeric vector

numeric vector

Functions

• .bouts2MLEll: Log likelihood function in a 2-process Poisson mixture

• .bouts3MLEll: Log likelihood function in a 3-process Poisson mixture

diveMove documentation built on Nov. 10, 2022, 5:11 p.m.