nll {quickNmix}

Negative Log Likelihood

Description

Computes the negative log likelihood function for the open population asymptotic N-mixtures model.

Usage

nll(
  par,
  nit,
  K,
  l_s_c = NULL,
  g_s_c = NULL,
  g_t_c = NULL,
  o_s_c = NULL,
  o_t_c = NULL,
  p_s_c = NULL,
  p_t_c = NULL,
  SMALL_a_CORRECTION = FALSE,
  VERBOSE = FALSE,
  outfile = NULL
)

Arguments

par

Vector of parameter values: c(log(lambda), log(gamma), logit(omega), logit(pdet)). Note that the parameter vector will need to be longer if covariate values are supplied.

nit

Matrix of counts data. Rows represent sites, columns represent sampling occasions. Note that if the data is a vector, then it will be converted to a matrix with a single row.

K

Upper bound on summations in the likelihood function. K should be chosen large enough that the negative log likelihood function is stable (unchanging as K increases).

l_s_c

List of lambda site covariates, Default: NULL

g_s_c

List of gamma site covariates, Default: NULL

g_t_c

List of gamma time covariates, Default: NULL

o_s_c

List of omega site covariates, Default: NULL

o_t_c

List of omega time covariates, Default: NULL

p_s_c

List of pdet site covariates, Default: NULL

p_t_c

List of pdet time covariates, Default: NULL

SMALL_a_CORRECTION

If TRUE will apply the small a correction when calculating the transition probability matrix, Default: FALSE

VERBOSE

If TRUE, will print additional information, Default: FALSE

outfile

Location of csv file to write/append parameter values, Default: NULL

Details

DETAILS

Value

Returns the negative log likelihood function evaluated at par.

Examples

if (interactive()) {
nit = matrix(c(1,1,0,1,1), nrow=1) # observations for 1 site, 5 sampling occassions
par = c(1,1,1,0) # parameter values at which to calculate the negative log likelihood (nll)
nll(par, nit, K=10) # nll with K=10
nll(par, nit, K=10, SMALL_a_CORRECTION=TRUE) # nll with small a correction
}