View source: R/outliers_replacer.R
outliers_replacer | R Documentation |
This function finds outliers in pollen time-series and replaces them with background values
outliers_replacer(value, date, threshold = 5, sum_percent = 100)
value |
pollen concentration values |
date |
dates |
threshold |
a number indicating how many times outlying value needs to be larger than the background to be replaced (default is 5) |
sum_percent |
a sum_percent parameter |
a new data.frame object with replaced outliers
Kasprzyk, I. and A. Walanus.: 2014. Gamma, Gaussian and Logistic Distribution Models for Airborne Pollen Grains and Fungal Spore Season Dynamics, Aerobiologia 30(4), 369-83.
data(pollen_count) df <- subset(pollen_count, site=='Shire') new_df <- outliers_replacer(df$birch, df$date) identical(df, new_df) library('purrr') new_pollen_count <- pollen_count %>% split(., .$site) %>% map_df(~outliers_replacer(value=.$hazel, date=.$date, threshold=4))
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