Exclude documentation .Rd of removed functions.

NAMESPACE

@@ -12,22 +12,14 @@ S3method(vcov,mcglm)
 export(fit_mcglm)
 export(mc_bias_corrected_std)
 export(mc_dexp_gold)
-export(mc_dfbetaOij)
-export(mc_fast_forward)
-export(mc_influence)
 export(mc_initial_values)
 export(mc_link_function)
 export(mc_matrix_linear_predictor)
-export(mc_qll)
 export(mc_quasi_score)
 export(mc_robust_std)
-export(mc_rw1)
-export(mc_rw2)
 export(mc_sic)
 export(mc_sic_covariance)
-export(mc_unstructured)
 export(mc_variance_function)
 export(mcglm)
-export(qic.mcglm)
 import(Matrix)
 import(assertthat)

man/mc_dfbetaOij.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_influence.R
-\name{mc_dfbetaOij}
-\alias{mc_dfbetaOij}
-\title{Influence measures for McGLMs}
-\usage{
-mc_dfbetaOij(Di, Ci, inv_Ci, ri, inv_M)
-}
-\arguments{
-\item{Di}{D matrix for the cluster i.}
-
-\item{Ci}{C matrix for the cluster i.}
-
-\item{inv_Ci}{Inverse of C matrix for the cluster i.}
-
-\item{ri}{Residual vector for the cluster i.}
-
-\item{inv_M}{Inverse of variance/covariance of regression parameters.}
-}
-\value{
-Matrix with the DFBETA for observation in the cluster i.
-}
-\description{
-Compute influence measures for multivariate covariance
-generalized linear models. Leverage, DFBETA and Cook's distance
-for observations. Auxiliar function for \code{mc_influence}.
-}
-\author{
-Wagner Hugo Bonat, \email{wbonat@ufpr.br}
-}
-

man/mc_fast_forward.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_fast_forward.R
-\name{mc_fast_forward}
-\alias{mc_fast_forward}
-\title{Fast forward selection for multivariate covariance generalized linear
-models.}
-\usage{
-mc_fast_forward(object, scope, interaction = 1, penalty = 2, n_max = 10)
-}
-\arguments{
-\item{object}{an object representing a model of \code{mcglm} class.}
-
-\item{scope}{a vector specyfing the covariate to be tested.}
-
-\item{interaction}{Maximum number of covariates interacting.}
-
-\item{penalty}{penalty term (default = 2).}
-
-\item{n_max}{Maximum number of models to be fitted.}
-}
-\value{
-The selected model.
-}
-\description{
-Perform fast forward model selection using the score
-information criterion. This function works only for univariate months.
-}
-

man/mc_influence.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_influence.R
-\name{mc_influence}
-\alias{mc_influence}
-\title{Influence measures for McGLMs}
-\usage{
-mc_influence(object, id)
-}
-\arguments{
-\item{object}{An object of \code{mcglm} class.}
-
-\item{id}{a vector which identifies the clusters.
-The length and order of id should match with the number of
-observations.}
-}
-\value{
-A list with influence measures for cluster and observations.
-}
-\description{
-Compute influence measures for multivariate covariance
-generalized linear models. Leverage, DFBETA and Cook's distance
-for unit sample and observations.
-}
-\author{
-Wagner Hugo Bonat, \email{wbonat@ufpr.br}
-}
-

man/mc_qll.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_qll.R
-\name{mc_qll}
-\alias{mc_qll}
-\title{Compute quasi-likelihood function.}
-\usage{
-mc_qll(y, mu, variance, power)
-}
-\arguments{
-\item{y}{A vector of observed values.}
-
-\item{mu}{A vector of fitted values.}
-
-\item{variance}{Variance function (constant, tweedie, poisson_tweedie, binomial).}
-
-\item{power}{Power parameter value.}
-}
-\value{
-The quasi-likelihood values.
-}
-\description{
-Given a variance function mc_qll function computes the quasi-likelihood values.
-}
-

man/mc_rw1.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_rw1.R
-\name{mc_rw1}
-\alias{mc_rw1}
-\title{Random walk first order model}
-\usage{
-mc_rw1(n_time, intrinsic = TRUE)
-}
-\arguments{
-\item{n_time}{Number observations time.}
-
-\item{intrinsic}{Logical indicating if the models is intrinsic (rho = 1) or not.}
-}
-\value{
-A matrix. Note that the function assumes that the data are in the correct order.
-}
-\description{
-Builds a random walk first order model matrix.
-}
-

man/mc_rw2.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_rw2.R
-\name{mc_rw2}
-\alias{mc_rw2}
-\title{Random walk second order model}
-\usage{
-mc_rw2(n_time, intrinsic = TRUE)
-}
-\arguments{
-\item{n_time}{Number observations time.}
-
-\item{intrinsic}{Logical indicating if the models is intrinsic (rho = 1) or not.}
-}
-\value{
-A matrix. Note that the function assumes that the data are in the correct order.
-}
-\description{
-Builds a random walk second order model matrix.
-}
-

man/mc_unstructured.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_unstructured.R
-\name{mc_unstructured}
-\alias{mc_unstructured}
-\title{Unstructured model}
-\usage{
-mc_unstructured(n_time)
-}
-\arguments{
-\item{n_time}{Number of observations per unit sample.}
-}
-\value{
-A matrix. Note that the function assumes that the data are in the correct order.
-}
-\description{
-Builds a unstructured model matrix.
-}
-

man/qic.mcglm.Rd

-% Generated by roxygen2 (4.1.1): do not edit by hand
-% Please edit documentation in R/mc_qic.R
-\name{qic.mcglm}
-\alias{qic.mcglm}
-\title{Compute Quasi Information Criterion (QIC) for McGLMs.}
-\usage{
-qic.mcglm(object, object.iid)
-}
-\arguments{
-\item{object}{An object of \code{mcglm} class.}
-
-\item{object.iid}{An object of \code{mcglm} class contained the model
-    fitted using independent covariance structure.}
-}
-\value{
-The QIC value.
-}
-\description{
-\code{qic.mcglm} is a function which computes the QIC
-    for McGLMs.
-}
-\author{
-Wagner Hugo Bonat, \email{wbonat@ufpr.br}
-}
-