#' This a function used to look at the IC.
#'
#' @param IC an influence curve evaluated at each observation
#' @return Histogram of the IC characteristics
#'
#' @importFrom dplyr group_by summarise
#' @importFrom tidyr pivot_longer
#' @importFrom ggplot2 ggplot aes geom_histogram geom_vline facet_wrap
#' @importFrom rlang .data
#'
#' @export
look_IC <- function(IC){
colnames(IC) <- 1:ncol(IC)
tidy_ic <- tidyr::pivot_longer(
as.data.frame(IC), cols = colnames(IC),
names_to = "Column")
mean_df <- dplyr::summarise(
dplyr::group_by(tidy_ic, .data$Column), mean = mean(.data$value)
)
ggplot2::ggplot(tidy_ic, ggplot2::aes(x = .data$value)) +
ggplot2::geom_histogram() +
ggplot2::geom_vline(data = mean_df, ggplot2::aes(xintercept = .data$mean)) +
ggplot2::facet_wrap(~as.numeric(.data$Column))
}
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