MLZ (version 0.1.5)

profile_ML: Grid search for the mean length estimator

Description

A grid search is performed over the time series, which can be used to identify local and global minima. A plot of the likelihood surface is also created similar to Figure 6 of Gedamke and Hoenig (2006) or Figure 3 of Huynh et al. (2017).

Usage

profile_ML(MLZ_data, ncp, startZ = rep(0.5, ncp + 1), min.time = 3,
  parallel = ifelse(ncp > 2, TRUE, FALSE), figure = TRUE,
  color = TRUE)

Value

A matrix of change points with the negative log-likelihood values.

Arguments

MLZ_data

An object of class MLZ_data.

ncp

The number of change points.

startZ

A vector of length ncp+1 as the starting value of total mortality rate used in the grid search.

min.time

The minimum number of years between change points. Only used if ncp > 1.

parallel

Whether grid search is performed using parallel processing.

figure

If TRUE, creates a plot of the likelihood over the grid search. Only used if ncp = 1 or 2.

color

If TRUE, creates a color plot for the likelihood surface. Only used if ncp = 2.

References

Gedamke, T. and Hoenig, J.M. 2006. Estimating mortality from mean length data in nonequilibrium situations, with application to the assessment of goosefish. Transactions of the American Fisheries Society 135:476-487.

Huynh, Q.C, Gedamke, T., Hoenig, J.M, and Porch C. 2017. Multispecies Extensions to a Nonequilibrium Length-Based Mortality Estimator. Marine and Coastal Fisheries 9:68-78.

Examples

if (FALSE) {
data(Goosefish)
profile_ML(Goosefish, ncp = 1)
profile_ML(Goosefish, ncp = 2)
}