R: Factor Copula Models

# Factor Copula Models

## Documentation for package ‘FactorCopulaModel’ version 0.1.1

- DESCRIPTION file

## Help Pages

bb1_cpar2td | BB1 copula parameter (theta,delta) to tail dependence parameters
bb1_tau2eqtd | BB1, given 0<tau<1, find theta and delta with lower tail dependence equal upper tail dependence
bb1_td2cpar | BB1 tail dependence parameters to copula parameter (theta,delta)
bifactor2cor | Bi-factor partial correlations to correlation matrix
bifactor2cor_v2 | Bi-factor partial correlations to correlation matrix version 2, using the inverse and determinant of a smaller matrix
bifactorcop_nllk | negative log-likelihood of bi-factor structured factor copula and derivatives computed in f90 for input to posDefHessMinb
bifactorEstWithProxy | Sequential parameter estimation for bi-factor copula with estimated latent variables using VineCopula::BiCopSelect
bifactorScore | Proxies for bi-factor copula model based on Gaussian bi-factor score
bifactor_fa | Gaussian bi-factor structure correlation matrix
bifactor_nllk | log-likelihood Gaussian bi-factor structure correlation matrix
bvnSemiCor | Semi-correlation for bivariate normal/Gaussian distribution
bvn_cpar2tau | Kendall's tau for bivariate normal
corDis | Discrepancy of model-based and observed correlation matrices based on Gaussian log-likelihood
corvec2mat | Convert from correlations in vector form to a correlation matrix
cparBounds | lower and upper bounds for copula parameters (1-parameter, 2-parameter families)
d1factcop | Integrand for 1-factor copula with 1-parameter bivariate linking copula families; or for m-parameter bivariate linking copulas
dateindex | GARCH-filtered log returns for Dow Jones stocks 2014-2016
dj1416gf | GARCH-filtered log returns for Dow Jones stocks 2014-2016
DJ20142016gf | GARCH-filtered log returns for Dow Jones stocks 2014-2016
euro07 | log returns and GARCH-filtered log returns for some Euro markets 2007
euro07gf | log returns and GARCH-filtered log returns for some Euro markets 2007
euro07names | log returns and GARCH-filtered log returns for some Euro markets 2007
factor1trvine_nllk | negative log-likelihood with gradient and Hessian computed in f90 for copula from 1-factor/1-truncated vine (tree for residual dependence conditional on a latent variable); models included are BB1 for latent with Frank or Gaussian(bvncop) for truncated vine residual dependence
frank_beta2cpar | Frank: Blomqvist's beta to copula parameter
frank_rhoS2cpar | Frank: Spearman rho to copula parameter
gauss1f1t | Compute correlation matrix according to 1-factor + 1-truncated vine (residual dependence) model
gaussLegendre | R interface for Gauss-Legendre quadrature
gumbel_beta2cpar | Gumbel: Blomqvist's beta to copula parameter
gumbel_rhoS2cpar | Gumbel: Spearman rho to copula parameter
isPosDef | Check if a square symmetric matrix is positive definite
lab | GARCH-filtered log returns for Dow Jones stocks 2014-2016
latentUpdate1factor | Compute new proxies for 1-factor copula based on the mean of observations
latentUpdate1factor1 | Compute new proxies for 1-factor copula based on the mean of observations
latentUpdateBifactor | Conditional expectation proxies for bi-factor copula models with linking copulas in different copula families
ml1factor | max likelihood (min negative log-likelihood) for 1-factor copula model
ml1factor_f90 | min negative log-likelihood for 1-factor copula with nlm()
ml1factor_v2 | min negative log-likelihood for 1-factor copula model (some parameters can be fixed)
mvtBifact | MLE for multivariate normal/t with a bi-factor or nested factor correlation structure
mvtBifact_nllk | negative log-likelihood for the bi-factor Gaussian/t model
mvtPfact | MLE in a MVt model with a p-factor correlation structure
mvtPfact_nllk | negative log-likelihood for the p-factor Gaussian/t model
nestfactorcop_nllk | negative log-likelihoods of nested factor structured factor copula and derivatives computed in f90 for input to posDefHessMinb
nscore | Rank-based normal scores transform
oblique_fa | Gaussian oblique factor structure correlation matrix
oblique_grad_fa | Gaussian oblique factor structure correlation matrix
oblique_grad_nllk | log-likelihood Gaussian oblique factor structure correlation matrix
oblique_nllk | log-likelihood Gaussian oblique factor structure correlation matrix
oblique_par2load | oblique factor correlation structure for d variables and m groups
oblique_pp_par2load | oblique factor correlation structure for d variables and m groups include determinant and inverse
onefactorcop_nllk | negative log-likelihood of 1-factor copula for input to posDefHessMin and posDefHessMinb
onefactorEstWithProxy | Parameter estimation for 1-factor copula with estimated latent variables using VineCopula::BiCopSeelct
pcor2load | Partial correlation representation to loadings for p-factor
pfactor_fa | Gaussian p-factor structure correlation matrix
pfactor_nllk | log-likelihood Gaussian p-factor structure correlation matrix
posDefHessMin | Minimization with modified Newton-Raphson iterations, Hessian is modified to be positive definite at each step. Algorithm and code produced by Pavel Krupskii (2013) see PhD thesis Krupskii (2014), UBC and Section 6.2 of # Joe (2014) Dependence Models with Copulas. Chapman&Hall/CRC
posDefHessMinb | Version with ifixed as argument
qcondbvtcop | C_[2|1]^[-1](p|u) for bivariate Student t copula
qcondFrank | C_[2|1]^[-1](p|u) for bivariate Frank copula
r1factor | simulate from 1-factor copula model with different linking copula families
rainstorm | Precipitation by rainstorm at 28 stations
rbifactor | simulate from bi-factor copula model
residDep | correlation matrix for 1-factor plus 1-truncated vine (for residual dependence)
rhoS | Spearman's rho for bivariate copula with parameter cpar
rmvn | Random multivariate normal (standard N(0,1) margins)
rmvt | Random multivariate t (standard t(nu) margins)
rnestfactor | Simulate data from nested copula or Gaussian model
RVtrunc2cor | compute correlation matrix from 2-truncated R-vine
semiCor | Semi-correlations for two variables
semiCorTable | Semi-correlation table for a multivariate data set
tailDep | Tail dependence parameter estimation
uscore | Rank-based uniform scores transform
zetaDep | Empirical version of zeta(alpha) tail-weighted dependence measure
zetaDepC | Upper Tail-weighted dependence measure zeta(C,alpha)
zetaPlot | Plot zeta(alpha) against alpha