R/1a_lm_data_prep.R

In bstaton1/FitSR: Functions to Fit and Summarize SRA Models

#' Prepare data for a linear SRA fit
#'
#' Takes the output of the \code{SimFit} functions to prepare
#' for fitting a linear regression model
#'
#' @param params a list object created by \code{SimFit::init_sim()} or \code{kusko_data_prep()$params}.
#'   Contains the driving parameters and dimensional variables.
#' @param obs a list object created by the functions that generate observations in the
#'   \code{SimFit} package or the \code{kusko_data_prep()$obs} function.
#'
#' @export

lm_data_prep = function(params, obs) {

  output = with(append(params, obs), {
    # brood year indices
    S_ind = 1:(nt - a_max)
    R_ind = (a_max + 1):(ny - na + 1)

    # indices for brood years to use
    S_ys_reg = S_ts_obs[S_ind,]
    R_ys_reg = R_ys_obs[R_ind,]

    # calculate log(RPS)
    log_RPS_ys = log(R_ys_reg/S_ys_reg)

    # bundle into a data.frame
    lm_dat = data.frame(log_RPS = as.numeric(log_RPS_ys), S_ys = as.numeric(S_ys_reg), stock = rep(1:ns, each = nrow(S_ys_reg)))
    lm_dat = lm_dat[!is.na(lm_dat$log_RPS),]

    list(
      ns = ns,
      nobs = nrow(lm_dat),
      obs_log_RPS_lme = lm_dat$log_RPS,
      obs_log_RPS_lm = lm_dat$log_RPS,
      S_obs = lm_dat$S_ys,
      stock = lm_dat$stock
    )
  })

  return(output)
}