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| Original file line number | Diff line number | Diff line change |
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| #' Create Pipster Object | ||
| #' | ||
| #' The first step in using the `pipster` package is to create a pipster object. | ||
| #' It creates the appropriate classes for welfare and weights, reformats the | ||
| #' data if necessary, and, for grouped data, it estimates and selects the lorenz | ||
| #' curves to be used for the estimation of poverty and distributional measures. | ||
| #' | ||
| #' @param welfare numeric: welfare vector | ||
| #' @param weight numeric: weight vector | ||
| #' @param imputation_id numeric: vector of ids for multiply imputed data. | ||
| #' Default is NULL | ||
| #' | ||
| #' @return list: pipster object containing welfare and weights, | ||
| #' params if grouped data, imputation_id if imputed data | ||
| #' @export | ||
| #' | ||
| #' @examples | ||
| #' p <- create_pipster_object(welfare = pip_gd$L, | ||
| #' weight = pip_gd$P) | ||
| #' p | ||
| create_pipster_object <- | ||
| function(welfare, | ||
| weight = rep(1, length(welfare)), | ||
| imputation_id = NULL) { | ||
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| #_____________________________________________________________________________ | ||
| # Arguments------------------------------------------------------------------- | ||
| if (is.na(welfare) |> any()) { | ||
| cli::cli_abort("No elements in welfare vector can be NA") | ||
| } | ||
| if (!is.numeric(welfare)) { | ||
| cli::cli_abort("welfare must be numeric") | ||
| } | ||
| if (length(weight) > 1 & any(is.na(weight))) { | ||
| cli::cli_abort("No elements in weight vector can be NA - | ||
| leave argument empty to give equal weighting") | ||
| } | ||
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| #_____________________________________________________________________________ | ||
| # Class----------------------------------------------------------------------- | ||
| tp <- identify_pip_type(welfare = welfare, | ||
| weight = weight, | ||
| imputation_id = imputation_id) | ||
| cl <- substr(tp, start = 1, stop = 2) | ||
| #_____________________________________________________________________________ | ||
| # Convert format-------------------------------------------------------------- | ||
| weight <- weight[order(welfare)] | ||
| welfare <- welfare[order(welfare)] | ||
| if (tp %in% c("gd_2", "gd_3", "gd_5")) { | ||
| welfare_original <- welfare | ||
| weight_original <- weight | ||
| } | ||
| switch( | ||
| tp, | ||
| "md" = { | ||
| imputation_id <- rep(1, length(welfare)) | ||
| }, | ||
| "id" = { | ||
| cl <- "md" | ||
| }, | ||
| "gd_1" = invisible(TRUE), | ||
| "gd_2" = { | ||
| welfare <- fcumsum(welfare)/fsum(welfare) | ||
| weight <- fcumsum(weight)/fsum(weight) | ||
| }, | ||
| "gd_3" = { | ||
| welfare <- fcumsum(welfare)/fsum(welfare) | ||
| }, | ||
| "gd_5" = { | ||
| welfare <- fcumsum(welfare)/fsum(welfare) | ||
| weight <- fcumsum(weight)/fsum(weight) | ||
| } | ||
| ) | ||
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| #_____________________________________________________________________________ | ||
| # Params---------------------------------------------------------------------- | ||
| if (cl == "gd") { | ||
| params <- pipgd_select_lorenz(welfare = welfare, | ||
| weight = weight, | ||
| complete = TRUE) | ||
| } | ||
|
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| #_____________________________________________________________________________ | ||
| # Return---------------------------------------------------------------------- | ||
| class_func <- paste0("new_pipster_", cl) |> | ||
| parse(text = _) | ||
| ret <- list( | ||
| welfare = eval(class_func)(welfare), | ||
| weight = eval(class_func)(weight) | ||
| ) | ||
| if (cl == "gd") { | ||
| ret$params <- params | ||
| } else { | ||
| ret$imputation_id <- imputation_id | ||
| } | ||
| class(ret) <- "pipster" | ||
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| ret | ||
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| } | ||
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