ce_quantiles {cepumd}

Calculate a CE weighted quantiles

Description

Calculate a CE weighted quantiles

Usage

ce_quantiles(ce_data, probs = 0.5)

Arguments

ce_data

A data frame containing at least a finlwt21 column and a cost column. Both columns must be numeric.

probs

A numeric vector of probabilities between 0 and 1 for which to compute quantiles. Default is 0.5 (median).

Value

A two-column data frame in which the first column contains the probabilities for which quantiles were calculated and their corresponding quantiles in the second column.

See Also

ce_mean()

Examples

## Not run: 
# Download the HG file keeping the section for expenditures on utilities
utils_hg <- ce_hg(2017, interview) |>
  ce_uccs("Utilities, fuels, and public services", uccs_only = FALSE)

# Download and prepare interview data
utils_interview <- ce_prepdata(
  2017,
  interview,
  uccs = ce_uccs(utils_hg, "Utilities, fuels, and public services"),
  zp = NULL,
  integrate_data = FALSE,
  hg = utils_hg,
  bls_urbn
)

# Calculate the 25%, 50%, and 75% utilities expenditure quantiles
ce_quantiles(utils_interview)

# Calculate the 25%, 50%, and 75% utilities expenditure quantiles by
# urbanicity
utils_interview |>
  tidyr::nest(-bls_urbn) |>
  mutate(quant_utils = purrr::map(data, ce_quantiles, c(0.25, 0.5, 0.75))) |>
  select(-data) |>
  unnest(quant_utils)

## End(Not run)