| gldFit | R Documentation | 
Estimates the distrinbutional parameters for a generalized lambda distribution.
gldFit(x, lambda1 = 0, lambda2 = -1, lambda3 = -1/8, lambda4 = -1/8, 
    method = c("mle", "mps", "gof", "hist", "rob"),
    scale = NA, doplot = TRUE, add = FALSE, span = "auto", trace = TRUE, 
    title = NULL, description = NULL, ...) 
x | 
 a numeric vector.  | 
lambda1, lambda2, lambda3, lambda4 | 
 are numeric values where
  | 
method | 
 a character string, the estimation approach to fit the distributional parameters, see details.  | 
scale | 
 not used.  | 
doplot | 
 a logical flag. Should a plot be displayed?  | 
add | 
 a logical flag. Should a new fit added to an existing plot?  | 
span | 
 x-coordinates for the plot, by default 100 values 
automatically selected and ranging between the 0.001, 
and 0.999 quantiles. Alternatively, you can specify
the range by an expression like   | 
trace | 
 a logical flag. Should the parameter estimation process be traced?  | 
title | 
 a character string which allows for a project title.  | 
description | 
 a character string which allows for a brief description.  | 
... | 
 parameters to be parsed.  | 
The function nlminb is used to minimize the objective 
function. The following approaches have been implemented:
"mle", maximimum log likelihoo estimation.
"mps", maximum product spacing estimation.
"gof", goodness of fit approaches, 
type="ad" Anderson-Darling, 
type="cvm" Cramer-vonMise,
type="ks" Kolmogorov-Smirnov.
"hist", histogram binning approaches,   
"fd" Freedman-Diaconis binning,
"scott", Scott histogram binning,
"sturges", Sturges histogram binning.
"rob", robust moment matching.
an object from class "fDISTFIT".
Slot fit is a list, currently with components
estimate, minimum and code.
set.seed(1953)
s <- rgld(n = 1000, lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8) 
gldFit(s, lambda1=0, lambda2=-1, lambda3=-1/8, lambda4=-1/8, 
       doplot = TRUE, trace = FALSE) 
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