Models for Correlation Matrices Based on Graphs

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Documentation for package ‘graphpcor’ version 0.1.12

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cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric.character 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric.default 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric.graphpcor 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric.treepcor 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric_generic0 Build an 'inla.cgeneric' to implement a model whose precision has a conditional precision parameter. See details. This uses the cgeneric interface that can be used as a model in a 'INLA' 'f()' model component.
cgeneric_get 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
cgeneric_graphpcor Build an 'inla.cgeneric' for a graph, see 'graphpcor()'
cgeneric_iid Build an 'inla.cgeneric' to implement a model whose precision has a conditional precision parameter. See details. This uses the cgeneric interface that can be used as a model in a 'INLA' 'f()' model component.
cgeneric_LKJ Build an 'inla.cgeneric' object to implement the LKG prior for the correlation matrix.
cgeneric_pc_correl Build an 'inla.cgeneric' to implement the PC prior, proposed on Simpson et. al. (2007), for the correlation matrix parametrized from the hypershere decomposition, see details.
cgeneric_pc_prec_correl Build an 'inla.cgeneric' to implement the PC-prior of a precision matrix as inverse of a correlation matrix.
cgeneric_treepcor Build an 'cgeneric' for 'treepcor()')
cgeneric_Wishart Build an 'inla.cgeneric' to implement the Wishart prior for a precision matrix.
chol-method Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
dim.graphpcor Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
dim.treepcor Set a tree whose nodes represent the two kind of variables: children and parent.
dLKJ The LKJ density for a correlation matrix
drop1-method Set a tree whose nodes represent the two kind of variables: children and parent.
dtheta Functions for the mapping between spherical and Euclidean coordinates.
edges-method Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
edges-method Set a tree whose nodes represent the two kind of variables: children and parent.
etreepcor2precision Set a tree whose nodes represent the two kind of variables: children and parent.
etreepcor2variance Set a tree whose nodes represent the two kind of variables: children and parent.
fillLprec Precision matrix parametrization helper functions.
graph 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
graph.inla.cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
graph.inla.rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
graphpcor The 'graphpcor' generic method for graphpcor
graphpcor-class Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
graphpcor.formula Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
graphpcor.matrix Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
hessian.graphpcor Evaluate the hessian of the KLD for a 'graphpcor' correlation model around a base model.
initial 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
initial.inla.cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
initial.inla.rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
inla.cgeneric-class 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
inla.rgeneric-class 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
is.zero Define the is.zero method
is.zero.default Define the is.zero method
is.zero.matrix Define the is.zero method
KLD10 Functions for the mapping between spherical and Euclidean coordinates.
kronecker-method 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
kronecker-method 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
Laplacian The Laplacian of a graph
Laplacian.default The Laplacian of a graph
Laplacian.graphpcor Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
Laplacian.matrix The Laplacian of a graph
Lprec Precision matrix parametrization helper functions.
mu 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
mu.inla.cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
mu.inla.rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
plot-method Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
plot-method Set a tree whose nodes represent the two kind of variables: children and parent.
prec The 'prec' method
prec.default The 'prec' method
prec.graphpcor Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
prec.inla The 'prec' method
prec.inla.cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
prec.inla.rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
prec.treepcor Set a tree whose nodes represent the two kind of variables: children and parent.
print.graphpcor Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
print.treepcor Set a tree whose nodes represent the two kind of variables: children and parent.
prior 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
prior.inla.cgeneric 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
prior.inla.rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
Q 'inla.cgeneric' class, short 'cgeneric', to define a 'INLA::cgeneric()' latent model
rcorrel Build the correlation matrix parametrized from the hypershere decomposition, see details.
rgeneric 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
rgeneric.default 'inla.rgeneric' class, short 'rgeneric', to define a 'INLA::rgeneric()' latent model
rphi2x Functions for the mapping between spherical and Euclidean coordinates.
rtheta Functions for the mapping between spherical and Euclidean coordinates.
summary.graphpcor Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
summary.treepcor Set a tree whose nodes represent the two kind of variables: children and parent.
theta2correl Build the correlation matrix parametrized from the hypershere decomposition, see details.
theta2gamma2L Build the correlation matrix parametrized from the hypershere decomposition, see details.
theta2H Functions for the mapping between spherical and Euclidean coordinates.
theta2Lprec2C Precision matrix parametrization helper functions.
treepcor Define a tree used to model correlation matrices using a shared latent variables method represented by a tree, whose nodes represent the two kind of variables: children and parent. See treepcor.
treepcor-class Set a tree whose nodes represent the two kind of variables: children and parent.
vcov-method Set a graph whose nodes and edges represent variables and conditional distributions, respectively.
vcov-method Set a tree whose nodes represent the two kind of variables: children and parent.
x2rphi Functions for the mapping between spherical and Euclidean coordinates.