fitteR: Fit Hundreds of Theoretical Distributions to Empirical Data
Systematic fit of hundreds of theoretical univariate distributions to empirical data via maximum likelihood estimation. Fits are reported and summarized by a data.frame, a csv file or a 'shiny' app (here with additional features like visual representation of fits). All output formats provide assessment of goodness-of-fit by the following methods: Kolmogorov-Smirnov test, Shapiro-Wilks test, Anderson-Darling test.
Version:
0.2.0
Depends:
R (≥ 3.3.0), methods
Suggests:
actuar,
ald,
benchden,
BiasedUrn,
bridgedist,
Davies,
DiscreteInverseWeibull,
DiscreteLaplace,
DiscreteWeibull,
emdbook,
emg,
EnvStats,
evd,
evir,
ExtDist,
extremefit,
FAdist,
FatTailsR,
fBasics,
fExtremes,
flexsurv,
gambin,
gb,
GenBinomApps,
GeneralizedHyperbolic,
gld,
GLDEX,
glogis,
GSM,
hermite,
HyperbolicDist,
KScorrect,
loglognorm,
marg,
mc2d,
minimax,
msm, nCDunnett,
NormalLaplace,
normalp,
ParetoPosStable,
PearsonDS,
poistweedie,
polyaAeppli,
qmap,
QRM,
ReIns,
reliaR,
Renext,
revdbayes,
RMKdiscrete,
RMTstat,
sadists,
skellam,
SkewHyperbolic,
skewt,
SMR,
sn,
stabledist, STAR,
statmod,
trapezoid,
triangle,
truncnorm,
VarianceGamma
Published:
2022年02月22日
Author:
Markus Boenn
Maintainer:
Markus Boenn <markus.boenn.sf at gmail.com>
NeedsCompilation:
no
Documentation:
Downloads:
Linking:
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