## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup, message=FALSE----------------------------------------------------- library(roundwork) ## ----------------------------------------------------------------------------- reround(x = c(5.812, 7.249), digits = 2, rounding = "up") ## ----------------------------------------------------------------------------- round_up(x = 1.24, digits = 1) round_up(x = 1.25, digits = 1) round_up(x = 1.25) # default for `digits` is 0 ## ----------------------------------------------------------------------------- round_up_from(x = 4.28, digits = 1, threshold = 9) round_up_from(x = 4.28, digits = 1, threshold = 1) ## ----------------------------------------------------------------------------- round_down(x = 1.24, digits = 1) round_down(x = 1.25, digits = 1) round_down(x = 1.25) # default for `digits` is 0 ## ----------------------------------------------------------------------------- round_down_from(x = 4.28, digits = 1, threshold = 9) round_down_from(x = 4.28, digits = 1, threshold = 1) ## ----------------------------------------------------------------------------- vec1 <- seq(from = 0.5, to = 9.5) up1 <- round_up(vec1) down1 <- round_down(vec1) even1 <- round(vec1) vec1 up1 down1 even1 # Original mean mean(vec1) # Means when rounding up or down: bias! mean(up1) mean(down1) # Mean when rounding to even: no bias mean(even1) ## ----------------------------------------------------------------------------- vec2 <- seq(from = 4.5, to = 10.5) up2 <- round_up(vec2) down2 <- round_down(vec2) even2 <- round(vec2) vec2 up2 down2 even2 # No symmetry here... mean(vec2) mean(up2) mean(down2) mean(even2) # ... and the mean is slightly biased downward! vec3 <- c( 1.05, 1.15, 1.25, 1.35, 1.45, 1.55, 1.65, 1.75, 1.85, 1.95 ) # No bias here, though: round(vec3, 1) mean(vec3) mean(round(vec3, 1)) ## ----------------------------------------------------------------------------- unround(x = "8.0") ## ----------------------------------------------------------------------------- unround(x = "3.50", rounding = "up") ## ----------------------------------------------------------------------------- unround(x = 3.5, digits = 2, rounding = "up") ## ----------------------------------------------------------------------------- vec2 <- c("2.0", "3.1", "3.5") vec2 %>% unround(rounding = "even") ## ----------------------------------------------------------------------------- reround_to_fraction(x = 0.4, denominator = 2, rounding = "up") ## ----------------------------------------------------------------------------- reround_to_fraction_level( x = 0.777, denominator = 5, digits = 0, rounding = "down" ) reround_to_fraction_level( x = 0.777, denominator = 5, digits = 1, rounding = "down" ) reround_to_fraction_level( x = 0.777, denominator = 5, digits = 2, rounding = "down" ) ## ----------------------------------------------------------------------------- vec3 <- seq(from = 0.6, to = 0.7, by = 0.01) vec3 # The mean before rounding... mean(vec3) # ...is not the same as afterwards... mean(round_up(vec3)) # ...and the difference is bias: rounding_bias(x = vec3, digits = 0, rounding = "up") ## ----------------------------------------------------------------------------- rounding_bias(x = vec3, digits = 0, rounding = "up", mean = FALSE) ## ----------------------------------------------------------------------------- vec4 <- rnorm(50000, 100, 15) rounding_bias(vec4, digits = 2) ## ----echo=FALSE--------------------------------------------------------------- up_1 <- rounding_bias(vec4, digits = 1, rounding = "up") up_2 <- rounding_bias(vec4, digits = 2, rounding = "up") up_3 <- rounding_bias(vec4, digits = 3, rounding = "up") up_4 <- rounding_bias(vec4, digits = 4, rounding = "up") up_5 <- rounding_bias(vec4, digits = 5, rounding = "up") even_1 <- rounding_bias(vec4, digits = 1, rounding = "even") even_2 <- rounding_bias(vec4, digits = 2, rounding = "even") even_3 <- rounding_bias(vec4, digits = 3, rounding = "even") even_4 <- rounding_bias(vec4, digits = 4, rounding = "even") even_5 <- rounding_bias(vec4, digits = 5, rounding = "even") bias <- abs(c( up_1, up_2, up_3, up_4, up_5, even_1, even_2, even_3, even_4, even_5 )) decimal_digits <- rep(1:5, 2) rounding <- c(rep("up", 5), rep("even", 5)) decimal_digits <- paste(decimal_digits, rounding) df <- tibble::tibble(bias, decimal_digits, rounding) # Display simulated data: df df <- df %>% dplyr::mutate( rounding = paste0("(", rounding, ")"), decimal_digits = paste(c(1:5, 1:5), rounding) # decimal_digits = paste0("(", decimal_digits, ")"), # rounding = paste0("(", rounding, ")") ) `%+replace%` <- ggplot2::`%+replace%` # Set ggplot2 theme for the remaining part of the session: ggplot2::theme_minimal(base_size = 12) %+replace% ggplot2::theme( panel.grid.major.x = ggplot2::element_blank(), panel.grid.minor.x = ggplot2::element_blank(), legend.position = "none" ) %>% ggplot2::theme_set() # Visualize: ggplot2::ggplot(df, ggplot2::aes(x = decimal_digits, y = bias, fill = rounding)) + ggplot2::geom_col(ggplot2::aes(fill = rounding)) + ggplot2::scale_y_continuous(expand = ggplot2::expansion(add = c(0, 0)) # labels = scales::comma ) + ggplot2::scale_fill_discrete(name = "Rounding") + ggplot2::labs( x = "Decimal places (rounding procedure)", y = "Mean absolute bias", title = "Directly from random numbers", subtitle = "Raw \"data\" mostly have 12 or 13 decimal places " ) ## ----echo=FALSE--------------------------------------------------------------- vec5 <- round(vec4, 2) up_1 <- rounding_bias(vec5, digits = 1, rounding = "up") up_2 <- rounding_bias(vec5, digits = 2, rounding = "up") up_3 <- rounding_bias(vec5, digits = 3, rounding = "up") up_4 <- rounding_bias(vec5, digits = 4, rounding = "up") up_5 <- rounding_bias(vec5, digits = 5, rounding = "up") even_1 <- rounding_bias(vec5, digits = 1, rounding = "even") even_2 <- rounding_bias(vec5, digits = 2, rounding = "even") even_3 <- rounding_bias(vec5, digits = 3, rounding = "even") even_4 <- rounding_bias(vec5, digits = 4, rounding = "even") even_5 <- rounding_bias(vec5, digits = 5, rounding = "even") bias <- abs(c( up_1, up_2, up_3, up_4, up_5, even_1, even_2, even_3, even_4, even_5 )) decimal_digits <- rep(1:5, 2) rounding <- c(rep("up", 5), rep("even", 5)) decimal_digits <- paste(decimal_digits, rounding) df_new <- tibble::tibble(bias, decimal_digits, rounding) # Display simulated data: df_new df_new <- df_new %>% dplyr::mutate( rounding = paste0("(", rounding, ")"), decimal_digits = paste(c(1:5, 1:5), rounding) # decimal_digits = paste0("(", decimal_digits, ")"), # rounding = paste0("(", rounding, ")") ) # Visualize: ggplot2::ggplot(df_new, ggplot2::aes(x = decimal_digits, y = bias, fill = rounding)) + ggplot2::geom_col(ggplot2::aes(fill = rounding)) + ggplot2::scale_y_continuous(expand = ggplot2::expansion(add = c(0, 0))) + ggplot2::scale_fill_discrete(name = "Rounding") + # ggplot2::theme_minimal() + # ggplot2::theme( # panel.grid.major.x = ggplot2::element_blank(), # panel.grid.minor.x = ggplot2::element_blank(), # legend.position = "none" # ) + ggplot2::labs( x = "Decimal places (rounding procedure)", y = "Mean absolute bias", title = "After previous rounding to 2 decimal places" )