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fgac (version 0.6-1)

Generalized Archimedean Copula

Description

Bi-variate data fitting is done by two stochastic components: the marginal distributions and the dependency structure. The dependency structure is modeled through a copula. An algorithm was implemented considering seven families of copulas (Generalized Archimedean Copulas), the best fitting can be obtained looking all copula's options (totally positive of order 2 and stochastically increasing models).

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Version

Install

install.packages('fgac')

Monthly Downloads

10

Version

0.6-1

License

GPL

Maintainer

Veronica Andrea GonzalezLopez

Last Published

October 29th, 2012

Functions in fgac (0.6-1)

dirac2

dirac2
dirac1

dirac1
FE2

FE2
SOB2

SOB2
FE1vector

FE1vector
pCBB7

pCBB7
phiBB7

phiBB7
ivphiBB3

ivphiBB3
ftest

ftest
ivphiBB1

ivphiBB1
pcopula2

pcopula2
pCMax

pCMax
cumulativemarg

cumulativemarg
fitCBB

fitCBB
KGalambos

KGalambos
ivpsiKS

ivpsiKS
ivphiBB2

ivphiBB2
phiBB1

phiBB1
phiBB3

phiBB3
diracS2

diracS2
fitlambdas

fitlambdas
pCBB2

pCBB2
phiBB6

phiBB6
ivphiBB7

ivphiBB7
psiKS

psiKS
ivphiBB6

ivphiBB6
pempirical

pempirical
pCMin

pCMin
pCBB1

pCBB1
fcopulamodel

fcopulamodel
pCBB4

pCBB4
phiBB2

phiBB2
psiGumbel

psiGumbel
diracS1

diracS1
pCBB3

pCBB3
ivpsiGumbel

ivpsiGumbel
pCBB6

pCBB6
pCBB5

pCBB5
OptimCBB

OptimCBB
pcopula1

pcopula1