Expand samples with quantiles
TO DO: implement using fitted() and predict() but avoid double-computing the samples? E.g.:
get_quantiles2 = function(fit, quantiles, facet_by = NULL) {
fitted(fit, probs = c(0.1, 0.5, 0.9), newdata = data.frame(x = c(11, 50, 100))) %>%
tidyr::pivot_longer(tidyselect::starts_with("Q")) %>%
dplyr::mutate(quantile = stringr::str_remove(name, "Q") %>% as.numeric() / 100)
}
get_quantiles(samples, quantiles, xvar, yvar, facet_by = NULL)
samples |
A tidybayes tibble |
quantiles |
Vector of quantiles (0.0 to 1.0) |
xvar |
An rlang::sym() with the name of the x-col in |
yvar |
An rlang::sym() with the name of the response col in |
facet_by |
String. Name of a varying group. |
A tidybayes long format tibble with the column "quantile"
Jonas Kristoffer Lindeløv jonas@lindeloev.dk
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