# How to find the best fitting distribution

    library(peppwR)

The package has one function for estimating the fit of a range of distributions `find_fits()`. It takes a data frame with at least three columns:

- `id_col` a unique id for the phosphopeptide
- `group_col` a category that groups measurements from the same bio replicate together
- `value_col` the measurment abundance/counts etc

    df_path <- system.file("raw_data.csv", package="peppwr")
    df <- readr::read_csv(df_path)

    fits_df <- find_fits(df, id_col="pep_id", group_col="group", value_col="value")

It returns a nested dataframe with elements for AIC and LogLikelihood of fit of each peptide’s counts to a range of distributions.

The result can be plot with `evaldist()`

    evaldist(fits_df)