Add citation for biorxiv

R/NobBS.R

@@ -8,8 +8,8 @@
 #' @param moving_window Size of moving window for estimation of cases. The moving window size should be specified in the same date units as the reporting data (i.e. specify 7 to indicate 7 days, 7 weeks, etc). Default: NULL, i.e. takes all historical dates into consideration.
 #' @param max_D Maximum possible delay observed or considered for estimation of the delay distribution. Default: (length of unique dates in time series)-1
 #' @param cutoff_D Consider only delays d<=\code{max_D}? Default: TRUE. If \code{cutoff_D=TRUE}, delays beyond \code{max_D} are ignored. If \code{cutoff_D=FALSE}, \code{max_D} is interpreted as delays>=\code{max_D} but within the moving window given by \code{moving_window}.
-#' @param specs A list with arguments specifying the Bayesian model used: \code{dist} (Default: "Poisson"), \code{beta.priors} (Default: 0.1 for each delay d), \code{nSamp} (Default: 10000), \code{nBurnin} (Default: 1000), \code{nAdapt} (Default: 1000), \code{nChains} (Default: 1), \code{nChains} (Default: 1), \code{nThin} (Default: 1), \code{alphat.shape.prior} (Default: 0.001), \code{alphat.rate.prior} (Default: 0.001), \code{alpha1.mean.prior} (Default: 0), \code{alpha1.prec.prior} (Default: 0.001), \code{dispersion.prior} (Default: NULL, i.e. no dispersion. Otherwise, enter c(shape,rate) for a Gamma distribution.), \code{conf} (Default: 0.95), \code{param_names} (Default: NULL, i.e. output for all parameters is provided: alpha[T], beta[d], lambda[T,d],and tau2.alpha). See McGough et al. 2018 (https://www.biorxiv.org/content/10.1101/663823v1) for detailed explanation of parameters.
-#' @return \code{NobBS} returns the list \code{nowcast_results} with the following elements: \code{estimates}, a Tx3 data frame containing estimates for each date in the time series (up to "now") with corresponding prediction intervals; \code{nowcast.post.samples}, vector of 10,000 samples from the posterior predictive distribution of the nowcast, and \code{params.post}, a 10,000x5 dataframe containing 10,000 posterior samples for each of the following parameters: \code{beta0}, \code{beta1}, \code{beta2}, \code{alpha[T]}, \code{tau2-alpha}.
+#' @param specs A list with arguments specifying the Bayesian model used: \code{dist} (Default: "Poisson"), \code{beta.priors} (Default: 0.1 for each delay d), \code{nSamp} (Default: 10000), \code{nBurnin} (Default: 1000), \code{nAdapt} (Default: 1000), \code{nChains} (Default: 1), \code{nChains} (Default: 1), \code{nThin} (Default: 1), \code{alphat.shape.prior} (Default: 0.001), \code{alphat.rate.prior} (Default: 0.001), \code{alpha1.mean.prior} (Default: 0), \code{alpha1.prec.prior} (Default: 0.001), \code{dispersion.prior} (Default: NULL, i.e. no dispersion. Otherwise, enter c(shape,rate) for a Gamma distribution.), \code{conf} (Default: 0.95), \code{param_names} (Default: NULL, i.e. output for all parameters is provided: alpha[T], beta[d], lambda[T,d],and tau2.alpha).
+#' @return \code{NobBS} returns the list \code{nowcast_results} with the following elements: \code{estimates}, a Tx3 data frame containing estimates for each date in the time series (up to "now") with corresponding prediction intervals; \code{nowcast.post.samples}, vector of 10,000 samples from the posterior predictive distribution of the nowcast, and \code{params.post}, a 10,000xN dataframe containing 10,000 posterior samples for the "N" parameters specified in specs[["param_names"]]. See McGough et al. 2019 (https://www.biorxiv.org/content/10.1101/663823v1) for detailed explanation of parameters.
 #' @examples
 #' Load the data
 #' data(denguedat)