R: Log likelihood function of parameters given observed data

boutsMLEll.chooser {diveMove} | R Documentation

## 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

[Package diveMove version 1.6.0 Index]