nlFitStart: Find Starting Values for Fitting a Normal Laplace...

View source: R/nlFitStart.R

nlFitStartR Documentation

Find Starting Values for Fitting a Normal Laplace Distribution

Description

Finds starting values for input to a maximum likelihood routine for fitting a normal Laplace distribution to data.

Usage

  nlFitStart(x, breaks = "FD",
             paramStart = NULL,
             startValues = c("MoM", "US"),
             startMethodMoM = "Nelder-Mead", ...)
  nlFitStartMoM(x, startMethodMoM = "Nelder-Mead", ...)

Arguments

x

Data vector.

breaks

Breaks for histogram. If missing, defaults to those generated by hist(x, right = FALSE, plot = FALSE).

paramStart

Starting values for parameter vector if startValues = "US".

startValues

Vector of the different starting value methods to consider. See Details.

startMethodMoM

Method used by call to optim in finding method of moments estimates.

...

Passes arguments to optim.

Details

Possible values of the argument startValues are the following:

"US"

User-supplied.

"MoM"

Method of moments.

If startValues = "US" then a value must be supplied for paramStart.

If startValues = "MoM", nlFitStartMoM is called.

If startValues = "MoM" an initial optimisation is needed to find the starting values. These optimisations call optim.

Value

nlFitStart returns a list with components:

paramStart

A vector with elements mu, sigma, alpha and beta giving the starting value of param.

xName

A character string with the actual x argument name.

breaks

The cell boundaries found by a call to hist.

midpoints

The cell midpoints found by a call to hist.

empDens

The estimated density found by a call to hist.

nlFitStartMoM returns only the method of moments estimates as a vector with elements mu, sigma, alpha and beta.

Author(s)

David Scott d.scott@auckland.ac.nz, Simon Potter

See Also

dnl, nlFit, hist, and optim.

Examples

param <- c(2, 2, 1, 1)
dataVector <- rnl(500, param = param)
nlFitStart(dataVector, startValues = "MoM")

NormalLaplace documentation built on Nov. 26, 2023, 1:07 a.m.