Nothing
knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(ssddata) library(ssdtools) library(ggplot2) dist <- ssdtools::ssd_fit_dists(ssddata::ccme_boron) pred <- predict(dist, ci = FALSE) ssdtools::ssd_plot_cdf(dist) + geom_line(data = pred, aes(x = est, y = percent/100))
An elegant approach using some tidyverse packages is demonstrated below.
library(ssddata) library(ssdtools) library(ggplot2) library(dplyr) library(tidyr) library(purrr) boron_preds <- nest(ccme_boron, data = c(Chemical, Species, Conc, Units)) %>% mutate( Fit = map(data, ssd_fit_dists, dists = "lnorm"), Prediction = map(Fit, predict) ) %>% unnest(Prediction)
The resultant data and predictions can then be plotted as follows.
ssd_plot(ccme_boron, boron_preds, xlab = "Concentration (mg/L)", ci = FALSE) + facet_wrap(~Group)
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