Apply the 72 rule.

R/mcglm.R

 ##' @title Multivariate covariance generalized linear models (McGLMs)
 ##'
-##'
-##' @description Fits a multivariate covariance generalized linear models (McGLMs) to data.
-##' McGLM is a general framework for non-normal multivariate data analysis, designed to handle
-##' multivariate response variables, along with a wide range of temporal and spatial correlation
-##' structures defined in terms of a covariance link function combined with a matrix linear predictor
-##' involving known matrices. The models take non-normality into account in the conventional way by means
-##' of a variance function, and the mean structure is modelled by means of a link function and a linear predictor.
-##' The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and
-##' Pearson estimating functions, using only second-moment assumptions.
-##' This provides a unified approach to a wide variety of different types of response variables and
-##' covariance structures, including multivariate extensions of repeated measures, time series, longitudinal,
-##' spatial and spatio-temporal structures.
-##'
+##' @description Fits a multivariate covariance generalized linear
+##'     models (McGLMs) to data.  McGLM is a general framework for
+##'     non-normal multivariate data analysis, designed to handle
+##'     multivariate response variables, along with a wide range of
+##'     temporal and spatial correlation structures defined in terms of
+##'     a covariance link function combined with a matrix linear
+##'     predictor involving known matrices. The models take
+##'     non-normality into account in the conventional way by means of a
+##'     variance function, and the mean structure is modelled by means
+##'     of a link function and a linear predictor.  The models are
+##'     fitted using an efficient Newton scoring algorithm based on
+##'     quasi-likelihood and Pearson estimating functions, using only
+##'     second-moment assumptions.  This provides a unified approach to
+##'     a wide variety of different types of response variables and
+##'     covariance structures, including multivariate extensions of
+##'     repeated measures, time series, longitudinal, spatial and
+##'     spatio-temporal structures.
 ##'
 ##' @docType package
 ##' @name mcglm
 NULL
 
-#' @name ahs
-#'
 #' @title Australian health survey
+#' @name ahs
 #'
-#' @description The Australian health survey was used by Bonat and Jorgensen (2015) as an example of multivariate
-#' count regression model. The data consists of five count response variables concerning health system access
-#' measures and nine covariates concerning  social conditions in Australian for 1987-88.
+#' @description The Australian health survey was used by Bonat and
+#'     Jorgensen (2015) as an example of multivariate count regression
+#'     model. The data consists of five count response variables
+#'     concerning health system access measures and nine covariates
+#'     concerning social conditions in Australian for 1987-88.
 #'
 #' \itemize{
+#'
 #' \item \code{sex} - Factor, two levels (0-Male; 1-Female).
+#'
 #' \item \code{age} - Respondent's age in years divided by 100.
-#'     \item \code{income} - Respondent's annual income in Australian dollars divided by 1000.
-#'     \item \code{levyplus} - Factor, two levels (1- if respondent is covered by private health
-#'     insurance fund for private patients in public hospital (with doctor of choice); 0 - otherwise).
-#'     \item \code{freepoor} - Factor, two levels (1 - if respondent is covered by government because low income,
-#'     recent immigrant, unemployed; 0 - otherwise).
-#'     \item \code{freerepa} - Factor, two levels (1 - if respondent is covered free by government because of
-#'     old-age or disability pension, or because invalid veteran or family of deceased veteran; 0 - otherwise).
-#'     \item \code{illnes} - Number of illnesses in past 2 weeks, with 5 or more weeks coded as 5.
-#'     \item \code{actdays} - Number of days of reduced activity in the past two weeks due to illness or injury.
-#'     \item \code{hscore} - Respondent's general health questionnaire score using Goldberg's method;
-#'     high score indicates poor health.
-#'     \item \code{chcond1} - Factor, two levels (1 - if respondent has chronic condition(s) but is not limited
-#'     in activity; 0 - otherwise).
-#'     \item \code{chcond2} - Factor, two levels (1 if respondent has chronic condition(s) and is limited in
-#'     activity; 0 - otherwise).
-#'     \item \code{Ndoc} - Number of consultations with a doctor or specialist (response variable).
-#'     \item \code{Nndoc} - Number of consultations with health professionals (response variable).
-#'     \item \code{Nadm} - Number of admissions to a hospital, psychiatric hospital, nursing or
-#'     convalescence home in the past 12 months (response variable).
-#'     \item \code{Nhosp} - Number of nights in a hospital during the most recent admission.
-#'     \item \code{Nmed} - Total number of prescribed and non prescribed medications used in the past two days.
+#'
+#' \item \code{income} - Respondent's annual income in Australian
+#'     dollars divided by 1000.
+#'
+#' \item \code{levyplus} - Factor, two levels (1- if respondent is
+#'     covered by private health insurance fund for private patients in
+#'     public hospital (with doctor of choice); 0 - otherwise).
+#'
+#' \item \code{freepoor} - Factor, two levels (1 - if respondent is
+#'     covered by government because low income, recent immigrant,
+#'     unemployed; 0 - otherwise).
+#'
+#' \item \code{freerepa} - Factor, two levels (1 - if respondent is
+#'     covered free by government because of old-age or disability
+#'     pension, or because invalid veteran or family of deceased
+#'     veteran; 0 - otherwise).
+#'
+#' \item \code{illnes} - Number of illnesses in past 2 weeks, with 5 or
+#'     more weeks coded as 5.
+#'
+#' \item \code{actdays} - Number of days of reduced activity in the past
+#'     two weeks due to illness or injury.
+#'
+#' \item \code{hscore} - Respondent's general health questionnaire score
+#'     using Goldberg's method; high score indicates poor health.
+#'
+#' \item \code{chcond1} - Factor, two levels (1 - if respondent has
+#'     chronic condition(s) but is not limited in activity; 0 -
+#'     otherwise).
+#'
+#' \item \code{chcond2} - Factor, two levels (1 if respondent has
+#'     chronic condition(s) and is limited in activity; 0 - otherwise).
+#'
+#' \item \code{Ndoc} - Number of consultations with a doctor or
+#'     specialist (response variable).
+#'
+#' \item \code{Nndoc} - Number of consultations with health
+#'     professionals (response variable).
+#'
+#' \item \code{Nadm} - Number of admissions to a hospital, psychiatric
+#'     hospital, nursing or convalescence home in the past 12 months
+#'     (response variable).
+#'
+#' \item \code{Nhosp} - Number of nights in a hospital during the most
+#'     recent admission.
+#'
+#' \item \code{Nmed} - Total number of prescribed and non prescribed
+#'     medications used in the past two days.
+#'
 #' \item \code{id} - Respondent's index.
+#'
 #' }
 #'
 #' @docType data
@@ -61,7 +97,8 @@ NULL
 #'
 #' @format a \code{data.frame} with 5190 records and 17 variables.
 #'
-#' @source Deb, P. and Trivedi, P. K. (1997). Demand for medical care by the elderly: A finite mixture approach,
-#' Journal of Applied Econometrics 12(3):313--336.
+#' @source Deb, P. and Trivedi, P. K. (1997). Demand for medical care by
+#'     the elderly: A finite mixture approach, Journal of Applied
+#'     Econometrics 12(3):313--336.
 #'
 NULL