combdist_plt function

Combined coefficients of power-law transformed combined distribution

Coefficients of a power-law transformed combined distribution

combdist_plt(
  dist,
  prior = NULL,
  coeff,
  a = 1,
  b = 1,
  inv = FALSE,
  nested = FALSE
)

Arguments

• dist: character vector denoting the distribution(s).
• prior: Numeric vector of prior coefficients, defaults to single vector with value one.
• coeff: list of parameters for the distribution(s).
• a, b: constant and power of power-law transformation, defaults to 1 and 1 respectively.
• inv: logical indicating whether coefficients of the outcome variable of the power-law transformation should be returned (FALSE) or whether coefficients of the input variable being power-law transformed should be returned (TRUE). Defaults to FALSE.
• nested: logical indicating whether results should be returned in a nested list or flat list, defaults to FALSE.

Returns

Returns a nested or flat list containing

• coefficients: Named vector of coefficients

Examples

# Load necessary tools
data("fit_US_cities")
library(tidyverse)

## Comparing probabilites of power-law transformed transformed variables
prob <- fit_US_cities %>%
  filter(!(dist %in% c(
    "exp", "invpareto_exp_pareto", "exp_pareto", "invpareto_exp",
    "gamma", "invpareto_gamma_pareto", "gamma_pareto", "invpareto_gamma"
  ))) %>%
  group_by(dist, components, np, n) %>%
  do(prob = pcombdist(q = 1.1, dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]])) %>%
  unnest(cols = c(prob))
fit_US_cities_plt <- fit_US_cities %>%
  filter(!(dist %in% c(
    "exp", "invpareto_exp_pareto", "exp_pareto", "invpareto_exp",
    "gamma", "invpareto_gamma_pareto", "gamma_pareto", "invpareto_gamma"
  ))) %>%
  group_by(dist, components, np, n, convergence) %>%
  do(results = as_tibble(combdist_plt(dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]], a = 2, b = 0.5, nested = TRUE))) %>%
  unnest(cols = c(results))
prob$prob_plt <- fit_US_cities_plt %>%
  group_by(dist, components, np, n) %>%
  do(prob_plt = pcombdist(q = 2 * 1.1^0.5, dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]])) %>%
  unnest(cols = c(prob_plt)) %>%
  .$prob_plt
prob <- prob %>%
  mutate(check = abs(prob - prob_plt))

prob <- fit_US_cities %>%
  filter(!(dist %in% c(
    "exp", "invpareto_exp_pareto", "exp_pareto", "invpareto_exp",
    "gamma", "invpareto_gamma_pareto", "gamma_pareto", "invpareto_gamma"
  ))) %>%
  group_by(dist, components, np, n) %>%
  do(prob = pcombdist(q = 2 * 1.1^0.5, dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]])) %>%
  unnest(cols = c(prob))
fit_US_cities_plt <- fit_US_cities %>%
  filter(!(dist %in% c(
    "exp", "invpareto_exp_pareto", "exp_pareto", "invpareto_exp",
    "gamma", "invpareto_gamma_pareto", "gamma_pareto", "invpareto_gamma"
  ))) %>%
  group_by(dist, components, np, n, convergence) %>%
  do(results = as_tibble(combdist_plt(dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]], a = 2, b = 0.5, nested = TRUE, inv = TRUE))) %>%
  unnest(cols = c(results))
prob$prob_plt <- fit_US_cities_plt %>%
  group_by(dist, components, np, n) %>%
  do(prob_plt = pcombdist(q = 1.1, dist = .[["dist"]], prior = .[["prior"]][[1]],
  coeff = .[["coefficients"]][[1]])) %>%
  unnest(cols = c(prob_plt)) %>%
  .$prob_plt
prob <- prob %>%
  mutate(check = abs(prob - prob_plt))