R/add_corcar.R

In nicholasjclark/mvgam: Multivariate (Dynamic) Generalized Additive Models

#' Updates for adding continuous time AR data
#' @noRd
add_corcar = function(model_data, data_train, data_test = NULL) {
  # Calculate temporal separation among observed points
  if (!is.null(data_test)) {
    all_times <- rbind(
      data.frame(
        series = as.numeric(data_train$series),
        time = data_train$time,
        index..time..index = data_train$index..time..index
      ),
      (data.frame(
        series = as.numeric(data_test$series),
        time = data_test$time,
        index..time..index = data_test$index..time..index
      ))
    ) %>%
      dplyr::group_by(series) %>%
      dplyr::arrange(index..time..index) %>%
      dplyr::mutate(
        time_lag = dplyr::lag(time),
        dis_time = time - time_lag,
        dis_time = ifelse(is.na(dis_time), 1, dis_time),
        dis_time = pmax(1e-3, dis_time)
      ) %>%
      dplyr::arrange(index..time..index, series)
  } else {
    all_times <- data.frame(
      series = as.numeric(data_train$series),
      time = data_train$time,
      index..time..index = data_train$index..time..index
    ) %>%
      dplyr::group_by(series) %>%
      dplyr::arrange(index..time..index) %>%
      dplyr::mutate(
        time_lag = dplyr::lag(time),
        dis_time = time - time_lag,
        dis_time = ifelse(is.na(dis_time), 1, dis_time),
        dis_time = pmax(1e-3, dis_time)
      ) %>%
      dplyr::ungroup() %>%
      dplyr::arrange(index..time..index, series)
  }

  time_dis <- matrix(
    NA,
    nrow = length(unique(all_times$index..time..index)),
    ncol = length(unique(all_times$series))
  )
  for (i in 1:length(unique(all_times$series))) {
    time_dis[, i] <- all_times$dis_time[which(all_times$series == i)]
  }

  model_data$time_dis <- time_dis

  return(model_data)
}