loess regression on each group with dplyr::group_by()

Question

Alright, I\'m waving my white flag.

I\'m trying to compute a loess regression on my dataset.

I want loess to compute a different set of points that plots a

Answer 1

This is a neat Tidyverse way to make it work:

library(dplyr)
library(tidyr)
library(purrr)
library(ggplot2)

models <- fems %>%
        tidyr::nest(-CpG) %>%
        dplyr::mutate(
                # Perform loess calculation on each CpG group
                m = purrr::map(data, loess,
                               formula = Meth ~ AVGMOrder, span = .5),
                # Retrieve the fitted values from each model
                fitted = purrr::map(m, `[[`, "fitted")
        )

# Apply fitted y's as a new column
results <- models %>%
        dplyr::select(-m) %>%
        tidyr::unnest()

# Plot with loess line for each group
ggplot(results, aes(x = AVGMOrder, y = Meth, group = CpG, colour = CpG)) +
        geom_point() +
        geom_line(aes(y = fitted))