riboHMM2: Analysis tool for Ribo-seq

#' uORF data
#'
#' An uORF dataset contains \code{num}=500 transcripts
#' generated by \code{generate_uORF} with parameters:
#' \itemize{
#'   \item  eL <- c(20, 36, 20, 96, 10)
#'   \item  eH <- c(5, 45,30,15, 40,20,10, 45,30,15,
#'                  5, 90,75,30, 60,50,20, 90,75,30, 5)
#'   \item  v <- rep(10, 21)
#'   \item  E <- c(rep(1,num/5), rep(5,num/5), rep(10,num/5),
#'                 rep(15,num/5), rep(20,num/5))
#'   \item  r <- 4
#' }
#' so \code{trans} = c(0.04, 0.01, 0.05) and \code{m} = eL / E
#'
#'
#' @format A list with 100 trajectories. Each list has variables as follows:
#' \describe{
#'   \item{z}{a vector. Hidden chain z}
#'   \item{x}{a vector. Observed chain x}
#'   \item{RNA}{a 0-1 vector. 1 if next 3-base is stop codon}
#'   \item{trans}{a vector. (rho, rho_u, delta)}
#'   \item{m}{a vector. mean parameter in gamma distribution for each state}
#'   \item{v}{a vector. Shape parameter in gamma distribution.}
#'   \item{E}{a scalar. Normalizing constant for the observed chain x}
#'   \item{stp}{a vector. (theta_u, theta) transition probability used}
#' }
"uORF"


#' pseudo_ribo data
#'
#' A pseudo_ribo dataset contains \code{num}=25000 transcripts
#' generated by \code{generate_ribo} with parameters:
#' \itemize{
#'   \item  eL <- c(20, 36, 20, 96, 10)
#'   \item  eH <- c(5, 45,30,15, 40,20,10, 45,30,15,
#'                  5, 90,75,30, 60,50,20, 90,75,30, 5)
#'   \item  v <- rep(10, 21)
#'   \item  E <- c(rep(1,num/5), rep(5,num/5), rep(10,num/5),
#'                 rep(15,num/5), rep(20,num/5))
#'   \item  p1, p2 = 0.8
#' }
#'
#'
#' @format A list with 25000 trajectories. Each list has variables as follows:
#' \describe{
#'   \item{z_base}{a vector. Hidden chain z}
#'   \item{z}{a vector. Hidden chain z}
#'   \item{x}{a vector. Observed chain x}
#'   \item{RNA}{a 0-1 vector. 1 if next 3-base is stop codon}
#'   \item{trans}{a vector. (rho, rho_u, delta)}
#'   \item{m}{a vector. mean parameter in gamma distribution for each state}
#'   \item{v}{a vector. Shape parameter in gamma distribution.}
#'   \item{E}{a scalar. Normalizing constant for the observed chain x}
#'   \item{stp}{a vector. (theta_u, theta) transition probability used}
#' }
"ribo"