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#' Standardized anomalies of CO Precipitation
#'
#' A dataset containing sample spatially-aggregated climate data from the
#' ERA-Interim and PRISM datasets. The response comes from PRISM, average
#' monthly precipitation in a DJF winter. The covariates come from ERA-Interim,
#' Colorado and Pacific Ocean (sea) surface temperatures. All data has been
#' converted to standardized anomalies.
#'
#' @format A stData object with 3 years of observations
#' \describe{
#' \item{tLabs}{year labels for data columns}
#' \item{coords.s}{centers of grid cells for Colorado data}
#' \item{coords.r}{centers of grid cells for Pacific Ocean data}
#' \item{X}{Array of design matrices for Colorado covariates}
#' \item{Y}{Matrix of precipitation observations}
#' \item{Z}{Matrix of Pacific Ocean data}
#' \item{X.lab}{Label for covariate data, used by plotting functions}
#' \item{Y.lab}{Label for response data, used by plotting functions}
#' \item{Z.lab}{Label for covariate data, used by plotting functions}
#' }
#'
#' @source \url{http://prism.oregonstate.edu}
#' @source \url{https://rda.ucar.edu/datasets/ds627.0/}
#'
#' @examples
#'
#' data("coprecip")
#' str(coprecip)
#'
"coprecip"
#' Sample MCMC output for the RESP model
#'
#' An example stFit object containing output from a short run of the MCMC
#' sampler that fits the RESP model to data.
#'
#'
#' @format An stFit object, which is a list of several objects
#' \describe{
#' \item{parameters}{MCMC samples of model parameters}
#' \item{priors}{description of priors used to fit model}
#' \item{miles}{TRUE or FALSE to specify whether the spatial distances
#' used to estimate spatial covariance parameters were in units of miles
#' (TRUE) or kilometers (FALSE)}
#' \item{localOnly}{TRUE if remote covariates were not estimated}
#' \item{remoteOnly}{TRUE if local covariates were not estimated}
#' \item{varying}{(deprecated) TRUE if local covariates were estimated as a
#' spatially-varying field}
#' \item{coords.knots}{coordinates of remote knot locations}
#' }
#'
#' @examples
#'
#' data("coprecip.fit")
#' str(coprecip.fit)
#'
"coprecip.fit"
#' Sample composition sampling output for the RESP model
#'
#' An example stPredict object containing predictions from a short run of the
#' MCMC composition sampler. The output also contains teleconnection estimates.
#'
#'
#' @format An stPredict object, which is a list of several objects
#' \describe{
#' \item{pred}{A list containing summaries of posterior predictions}
#' \item{samples}{Posterior samples for predictions}
#' \item{coords.s}{centers of grid cells for Colorado data}
#' \item{localOnly}{TRUE if remote covariates were not estimated}
#' \item{varying}{(deprecated) TRUE if local covariates were estimated as a
#' spatially-varying field}
#' \item{tLabs}{year labels for prediction timepoints}
#' \item{Y.lab}{Label for response data, used by plotting functions}
#' \item{cat.probs}{vector of probabilities for using posterior samples to
#' return categorical predictions from the posterior prediction samples}
#' \item{category.breaks}{Breakpoints used to discretize posterior predictive
#' distribution at each coordinate in coords.s during composition sampling.}
#' \item{alpha_knots}{Summaries of posterior estimates of teleconnection
#' effects}
#' \item{eof_alpha_knots}{Summaries of posterior estimates of teleconnection
#' effects after spatial basis function transformation}
#' }
#'
#' @examples
#'
#' data("coprecip.predict")
#' str(coprecip.predict)
#'
"coprecip.predict"
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