feature/car

DESCRIPTION

@@ -7,23 +7,23 @@ Encoding: UTF-8
 Authors@R: c(person("Jonah", "Gabry", email = "[email protected]", role = "aut"),
              person("Imad", "Ali", role = "ctb"),
              person("Sam", "Brilleman", role = "ctb"),
-             person(given = "Jacqueline Buros", family = "Novik", 
+             person(given = "Jacqueline Buros", family = "Novik",
                     role = "ctb", comment = "R/stan_jm.R"),
              person("AstraZeneca", role = "ctb", comment = "R/stan_jm.R"),
              person("Trustees of", "Columbia University", role = "cph"),
              person("Simon", "Wood", role = "cph", comment = "R/stan_gamm4.R"),
-             person("R Core", "Deveopment Team", role = "cph", 
+             person("R Core", "Deveopment Team", role = "cph",
                      comment = "R/stan_aov.R"),
              person("Douglas", "Bates", role = "cph", comment = "R/pp_data.R"),
              person("Martin", "Maechler", role = "cph", comment = "R/pp_data.R"),
              person("Ben", "Bolker", role = "cph", comment = "R/pp_data.R"),
              person("Steve", "Walker", role = "cph", comment = "R/pp_data.R"),
-             person("Brian", "Ripley", role = "cph", 
+             person("Brian", "Ripley", role = "cph",
                     comment = "R/stan_aov.R, R/stan_polr.R"),
              person("William", "Venables", role = "cph", comment = "R/stan_polr.R"),
              person("Paul-Christian", "Burkner", email = "[email protected]",
                     role = "cph", comment = "R/misc.R"),
-             person("Ben", "Goodrich", email = "[email protected]", 
+             person("Ben", "Goodrich", email = "[email protected]",
                     role = c("cre", "aut")))
 Description: Estimates previously compiled regression models using the 'rstan'
     package, which provides the R interface to the Stan C++ library for Bayesian
@@ -54,6 +54,7 @@ Suggests:
     digest,
     gridExtra,
     HSAUR3,
+    INLA,
     knitr (>= 1.15.1),
     MASS,
     mgcv (>= 1.8-13),

NAMESPACE

@@ -89,10 +89,12 @@ S3method(update,stanmvreg)
 S3method(update,stanreg)
 S3method(vcov,stanreg)
 S3method(waic,stanreg)
+export()
 export(R2)
 export(Surv)
 export(VarCorr)
 export(bayes_R2)
+export(beta)
 export(cauchy)
 export(compare_models)
 export(decov)
@@ -148,6 +150,7 @@ export(ranef)
 export(se)
 export(sigma)
 export(stan_aov)
+export(stan_besag)
 export(stan_betareg)
 export(stan_betareg.fit)
 export(stan_biglm)
@@ -168,6 +171,7 @@ export(stan_mvmer)
 export(stan_nlmer)
 export(stan_polr)
 export(stan_polr.fit)
+export(stan_spatial.fit)
 export(stanjm_list)
 export(stanmvreg_list)
 export(stanreg_list)

R/doc-datasets.R

@@ -1,34 +1,34 @@
 # Part of the rstanarm package for estimating model parameters
 # Copyright (C) 2015, 2016, 2017 Trustees of Columbia University
-# 
+#
 # This program is free software; you can redistribute it and/or
 # modify it under the terms of the GNU General Public License
 # as published by the Free Software Foundation; either version 3
 # of the License, or (at your option) any later version.
-# 
+#
 # This program is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 # GNU General Public License for more details.
-# 
+#
 # You should have received a copy of the GNU General Public License
 # along with this program; if not, write to the Free Software
 # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
 #
 #' Datasets for rstanarm examples
-#' 
+#'
 #' Small datasets for use in \pkg{rstanarm} examples and vignettes.
 #'
 #' @name rstanarm-datasets
 #' @aliases kidiq roaches wells bball1970 bball2006 mortality tumors radon pbcLong pbcSurv
-#' @format 
+#' @format
 #' \describe{
 #' \item{\code{bball1970}}{
 #' Data on hits and at-bats from the 1970 Major League Baseball season for 18
 #' players.
-#' 
+#'
 #' Source: Efron and Morris (1975).
-#' 
+#'
 #' 18 obs. of 5 variables
 #' \itemize{
 #' \item \code{Player} Player's last name
@@ -41,21 +41,21 @@
 #' \item{\code{bball2006}}{
 #' Hits and at-bats for the entire 2006 American League season of Major League
 #' Baseball.
-#' 
+#'
 #' Source: Carpenter (2009)
-#' 
+#'
 #' 302 obs. of 2 variables
 #' \itemize{
 #' \item \code{y} Number of hits
 #' \item \code{K} Number of at-bats
 #' }
 #' }
 #' \item{\code{kidiq}}{
-#' Data from a survey of adult American women and their children 
+#' Data from a survey of adult American women and their children
 #' (a subsample from the National Longitudinal Survey of Youth).
-#' 
+#'
 #' Source: Gelman and Hill (2007)
-#' 
+#'
 #' 434 obs. of 4 variables
 #' \itemize{
 #' \item \code{kid_score} Child's IQ score
@@ -67,7 +67,7 @@
 #' \item{\code{mortality}}{
 #' Surgical mortality rates in 12 hospitals performing cardiac surgery
 #' in babies.
-#' 
+#'
 #' Source: Spiegelhalter et al. (1996).
 #'
 #' 12 obs. of 2 variables
@@ -77,38 +77,38 @@
 #' }
 #' }
 #' \item{\code{pbcLong,pbcSurv}}{
-#' Longitudinal biomarker and time-to-event survival data for 40 patients 
-#' with primary biliary cirrhosis who participated in a randomised 
+#' Longitudinal biomarker and time-to-event survival data for 40 patients
+#' with primary biliary cirrhosis who participated in a randomised
 #' placebo controlled trial of D-penicillamine conducted at the Mayo
 #' Clinic between 1974 and 1984.
-#' 
+#'
 #' Source: Therneau and Grambsch (2000)
-#' 
+#'
 #' 304 obs. of 8 variables (\code{pbcLong}) and 40 obs. of 7 variables (\code{pbcSurv})
 #' \itemize{
 #' \item \code{age} {in years}
 #' \item \code{albumin} {serum albumin (g/dl)}
 #' \item \code{logBili} {logarithm of serum bilirubin}
-#' \item \code{death} {indicator of death at endpoint} 
-#' \item \code{futimeYears} {time (in years) between baseline and  
+#' \item \code{death} {indicator of death at endpoint}
+#' \item \code{futimeYears} {time (in years) between baseline and
 #'     the earliest of death, transplantion or censoring}
 #' \item \code{id} {numeric ID unique to each individual}
 #' \item \code{platelet} {platelet count}
 #' \item \code{sex} {gender (m = male, f = female)}
-#' \item \code{status} {status at endpoint (0 = censored, 
+#' \item \code{status} {status at endpoint (0 = censored,
 #'     1 = transplant, 2 = dead)}
-#' \item \code{trt} {binary treatment code (0 = placebo, 1 = 
+#' \item \code{trt} {binary treatment code (0 = placebo, 1 =
 #'     D-penicillamine)}
 #' \item \code{year} {time (in years) of the longitudinal measurements,
 #'     taken as time since baseline)}
 #' }
 #' }
-#' 
+#'
 #' \item{\code{radon}}{
-#' Data on radon levels in houses in the state of Minnesota. 
-#' 
+#' Data on radon levels in houses in the state of Minnesota.
+#'
 #' Source: Gelman and Hill (2007)
-#' 
+#'
 #' 919 obs. of 4 variables
 #' \itemize{
 #' \item \code{log_radon} Radon measurement from the house (log scale)
@@ -121,9 +121,9 @@
 #' \item{\code{roaches}}{
 #' Data on the efficacy of a pest management system at reducing the number of
 #' roaches in urban apartments.
-#' 
+#'
 #' Source: Gelman and Hill (2007)
-#' 
+#'
 #' 262 obs. of 6 variables
 #' \itemize{
 #' \item \code{y} Number of roaches caught
@@ -136,10 +136,10 @@
 #' \item{\code{tumors}}{
 #' Tarone (1982) provides a data set of tumor incidence in historical
 #' control groups of rats; specifically endometrial stromal polyps in
-#' female lab rats of type F344.  
-#' 
+#' female lab rats of type F344.
+#'
 #' Source: Gelman and Hill (2007)
-#' 
+#'
 #' 71 obs. of 2 variables
 #' \itemize{
 #' \item \code{y} Number of rats with tumors
@@ -153,9 +153,9 @@
 #' safe public or private well in the nearby area and the survey was conducted
 #' several years later to learn which of the affected residents had switched
 #' wells.
-#' 
+#'
 #' Souce: Gelman and Hill (2007)
-#' 
+#'
 #' 3020 obs. of 5 variables
 #' \itemize{
 #' \item \code{switch} Indicator for well-switching
@@ -167,27 +167,46 @@
 #' \item \code{educ} Years of education (head of household)
 #' }
 #' }
+#' \item{\code{lattice}}{ The \code{grid_sim15} and \code{grid_sim30}
+#' SpatialPolygonsDataFrame objects are a simulated lattice of 225 and 900
+#' spatial units, respectively. These objects contain spatially dependent
+#' observations simulated as a Gaussian Markov Random Field (GMRF). The data
+#' slot in \code{grid_sim15} contains simulated outcomes using the GMRF and
+#' various supported likelihoods.
+#'
+#' Source: Simulated data
+#'
+#' \itemize{
+#' \item \code{gmrf} GMRF data simulated using Cholesky decomposition sampling
+#' from the precision form of the Multivariate Normal distribution centered at
+#' zero.
+#' \item \code{r} X-position of a location on the grid (origin is at the
+#' bottom-left).
+#' \item \code{c} Y-position of a location on the grid (origin is at the
+#' bottom-left).
 #' }
-#' 
-#' @references 
+#' }
+#' }
+#'
+#' @references
 #' Carpenter, B. (2009) Bayesian estimators for the beta-binomial model of
 #' batting ability. \url{http://lingpipe-blog.com/2009/09/23/}
-#' 
+#'
 #' Efron, B. and Morris, C. (1975) Data analysis using Stein's estimator and its
 #' generalizations. \emph{Journal of the American Statistical Association}
 #' \strong{70}(350), 311--319.
-#' 
+#'
 #' @templateVar armRef \url{http://stat.columbia.edu/~gelman/arm/}
 #' @template reference-gelman-hill
-#' 
+#'
 #' @references
-#' Spiegelhalter, D., Thomas, A., Best, N., & Gilks, W. (1996) BUGS 0.5 
+#' Spiegelhalter, D., Thomas, A., Best, N., & Gilks, W. (1996) BUGS 0.5
 #' Examples. MRC Biostatistics Unit, Institute of Public health, Cambridge, UK.
-#' 
+#'
 #' Tarone, R. E. (1982) The use of historical control information in testing for
 #' a trend in proportions. \emph{Biometrics} \strong{38}(1):215--220.
-#' 
-#' Therneau, T. and Grambsch, P. (2000) \emph{Modeling Survival Data: Extending 
+#'
+#' Therneau, T. and Grambsch, P. (2000) \emph{Modeling Survival Data: Extending
 #' the Cox Model}. Springer-Verlag, New York, US.
 #' 
 #' @examples
@@ -200,7 +219,7 @@
 #' pp_check(fit, nreps = 20)
 #' \donttest{
 #' bayesplot::color_scheme_set("brightblue")
-#' pp_check(fit, plotfun = "stat_grouped", stat = "median", 
+#' pp_check(fit, plotfun = "stat_grouped", stat = "median",
 #'          group = factor(kidiq$mom_hs, labels = c("No HS", "HS")))
 #' }
 #' }