MLEZ: Fitting parameters of PDF by means of maximum likelihood

Description Usage Arguments Value Examples

View source: R/MLEZ.R

Description

This function fits parameters of probability distribution functions (see selecDIST) by means of maximum likelihood and performs evolutionary global optimization via the Differential Evolution algorithm (see DEoptim package).

Usage

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MLEZ(Intensity, type, para.int = NULL, silent = TRUE,
  null.on.not.converge = TRUE, ptransf = function(t) return(t),
  pretransf = function(t) return(t))

Arguments

Intensity:

a numeric vector with intensity [mm/h] values of different years for a specific time duration (e.g. 5, 15, 120 minutes, etc.).

type:

a character specifying the name of the distribution function that will be employed: exponencial, gamma, gev, gumbel, log.normal3, normal, pearson, log.pearson3 and wakeby (see selecDIST).

para.int:

Initial parameters as a vector Θ.

silent:

a logical to silence the try function wrapping the DEoptim function.

null.on.not.converge:

a logical to trigger simple return of NULL if the DEoptim function returns a nonzero convergence status.

Value

A list of:

Examples

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data(inten)
TEST.MLE <- MLEZ(Intensity = inten[,4], type = "Gumbel", para.int = NULL, silent = TRUE, null.on.not.converge = TRUE, 
                 ptransf = function(t) return(t), pretransf = function(t) return(t))

## Results: xi = 71.178 ; alpha = 15.204 

dazamora/IDFtool documentation built on March 20, 2018, 8:56 p.m.