Fitting univariate distributions by maximum likelihood or by matching moments
Description
Fits a univariate distribution by maximum likelihood or by matching moments.
Usage
1 2  rriskFitdist.cont(data, distr, method = c("mle", "mme"), start,
chisqbreaks, meancount, ...)

Arguments
data 
A numerical vector, data to be fitted. 
distr 
A character string 
method 
A character string coding for the fitting method: "mle" for the maximum likelihood estimation and "mme" for the matching moment estimation. 
start 
A named list giving the initial values of parameters of the named
distribution. This argument will not be taken into account if 
chisqbreaks 
A numerical vector defining the breaks of the cell used to
compute the chisquare statistic. If omitted, these breaks are automatically
computed from the data in order to reach roughly the same number of observations
per cell, roughly equal to the argument 
meancount 
The mean number of observations per cell expected for the definition of the breaks of the cells used to compute the chisquared statistic. 
... 
further arguments to be passed to generic function, or to the
function 
Details
This function is an alias of the function fitdist
from the package
fitdistrplus (Version 0.12). The original function was extended to
fitting additional distributions. The following continuous distributions can
be fitted by this function: normal, lognormal, logistic, exponential, F,
Student's t, Beta, Cauchy, Weibull, Gamma.
For more details see the assistance page of the function
fitdist
from the package fitdistrplus.
This function is not intended to be called directly but is internally
called in useFitdist
.
Value
rriskFitdist.cont
returns a list containing 19 items with following fitting results:

numeric, a single value or a vector containing estimated parameters. 

the character string representing the used fitting method ("mle" or "mme"). 

the estimated standard errors or 

the estimated correlation matrix or 

the loglikelihood or 

the Akaike information criterion or 

the BIC or SBC (Schwarz Bayesian criterion) or 

the length of the data set. 

the data set. 

the name of the estimated distribution. 

the Chisquared statistic or 

breaks used to define cells in the chisquare statistic. 

pvalue of the chisquare statistic or 

degree of freedom of the chisquare distribution or 

a table with observed and theoretical counts used for the Chisquared calculations. 

the AndersonDarling statistic or 

the decision of the AndersonDarling test or 

the KolmogorovSmirnov statistic or 

the decision of the KolmogorovSmirnov test or 
Author(s)
Matthias Greiner matthias.greiner@bfr.bund.de (BfR),
Kristin Tolksdorf kristin.tolksdorf@bfr.bund.de (BfR),
Katharina Schueller schueller@statup.de (STATUP Statistical Consulting),
Natalia Belgorodski belgorodski@statup.de (STATUP Statistical Consulting)
MarieLaure DelignetteMuller (coauthor of the package fitdistrplus)
Christophe Dutang (coauthor of the package fitdistrplus)
Examples
1 2 3 4  set.seed(1)
x < stats::rnorm(5000, mean = 10, sd = 5)
rriskFitdist.cont(x, "norm")
rriskFitdist.cont(x, "t")

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