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Fixes #362
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#' Distribution Statistics | ||
#' | ||
#' @family Triangular | ||
#' @family Distribution Statistics | ||
#' | ||
#' @author Steven P. Sanderson II, MPH | ||
#' | ||
#' @details This function will take in a tibble and returns the statistics | ||
#' of the given type of `tidy_` distribution. It is required that data be | ||
#' passed from a `tidy_` distribution function. | ||
#' | ||
#' @description Returns distribution statistics in a tibble. | ||
#' | ||
#' @param .data The data being passed from a `tidy_` distribution function. | ||
#' | ||
#' @examples | ||
#' library(dplyr) | ||
#' | ||
#' tidy_triangular() |> | ||
#' util_triangular_stats_tbl() |> | ||
#' glimpse() | ||
#' | ||
#' @return | ||
#' A tibble | ||
#' | ||
#' @name util_triangular_stats_tbl | ||
NULL | ||
#' @export | ||
#' @rdname util_triangular_stats_tbl | ||
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util_triangular_stats_tbl <- function(.data) { | ||
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# Immediate check for tidy_ distribution function | ||
if (!"tibble_type" %in% names(attributes(.data))) { | ||
rlang::abort( | ||
message = "You must pass data from the 'tidy_dist' function.", | ||
use_cli_format = TRUE | ||
) | ||
} | ||
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if (attributes(.data)$tibble_type != "tidy_triangular") { | ||
rlang::abort( | ||
message = "You must use 'tidy_chisquare()'", | ||
use_cli_format = TRUE | ||
) | ||
} | ||
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# Data | ||
data_tbl <- dplyr::as_tibble(.data) | ||
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atb <- attributes(data_tbl) | ||
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a <- atb$.min | ||
b <- atb$.mode | ||
c <- atb$.max | ||
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stat_mean <- (a + b + c) / 3 | ||
stat_median <- if (c >= (a+b)/2) { | ||
(a + (sqrt((b-a)*(c-a))/2)) | ||
} else { | ||
(b - (sqrt((b-1)*(b-c))/2)) | ||
} | ||
stat_mode <- c | ||
stat_range <- range(data_tbl$y) | ||
stat_variance <- ((a^2) + (b^2) + (c^2) - (a*b) - (a*c) - (b*c)) / 18 | ||
stat_skewness <- ((sqrt(2) * (a + b - (2*c))) * ((2*a) - b - c) * (a - 2*b +c)) / 5*(a^2 + b^2 + c^2 - a*b - a*c - b*c)^(3/2) | ||
stat_kurtosis <- -(3/5) | ||
stat_entropy <- 0.5 * log((b-a)/2) | ||
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# Data Tibble | ||
ret <- dplyr::tibble( | ||
tidy_function = atb$tibble_type, | ||
function_call = atb$dist_with_params, | ||
distribution = dist_type_extractor(atb$tibble_type), | ||
distribution_type = atb$distribution_family_type, | ||
points = atb$.n, | ||
simulations = atb$.num_sims, | ||
mean = stat_mean, | ||
median = stat_median, | ||
mode = stat_mode, | ||
range_low = stat_range[[1]], | ||
range_high = stat_range[[2]], | ||
variance = stat_variance, | ||
skewness = stat_skewness, | ||
kurtosis = stat_kurtosis, | ||
entropy = stat_entropy, | ||
computed_std_skew = tidy_skewness_vec(data_tbl$y), | ||
computed_std_kurt = tidy_kurtosis_vec(data_tbl$y), | ||
ci_lo = ci_lo(data_tbl$y), | ||
ci_hi = ci_hi(data_tbl$y) | ||
) | ||
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# Return | ||
return(ret) | ||
} |
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