MazamaRollUtils
MazamaRollUtils provides fast rolling-window ("moving") functions for numeric vectors, backed by compiled C++ (Rcpp). It covers the familiar rolling statistics — mean, median, min, max, sum, product, standard deviation, variance — along with a Median Absolute Deviation, a Hampel filter, and the US EPA NowCast.
The package is designed for efficient processing of environmental time series such as hourly air-quality data. It deliberately operates on plain numeric vectors with no underlying data model, so it composes with any workflow, and every rolling function returns a vector the same length as its input.
Installation
Install the released version from CRAN:
install.packages("MazamaRollUtils")Install the development version from GitHub:
remotes::install_github("MazamaScience/MazamaRollUtils")Example
Apply a rolling mean and a rolling max/min envelope to the hourly PM2.5 air-quality series included with the package:
library(MazamaRollUtils)
t <- example_pm25$datetime
x <- example_pm25$pm25
plot(t, x, pch = 16, cex = 0.5, col = "gray60")
lines(t, roll_mean(x, width = 12), col = "black", lwd = 2)
lines(t, roll_max(x, width = 12), col = "salmon")
lines(t, roll_min(x, width = 12), col = "steelblue")Overview
- Rolling statistics —
roll_mean(),roll_median(),roll_max(),roll_min(),roll_sum(),roll_prod(),roll_sd(),roll_var() - Robust measures and outlier detection —
roll_MAD()(Median Absolute Deviation),roll_hampel()(Hampel filter),findOutliers()(indices of outliers flagged by a rolling Hampel filter) - Domain-specific calculations —
roll_nowcast()(US EPA NowCast for hourly particulate matter)
The roll_*() functions share the arguments width, by, align, and, where
statistically meaningful, na.rm and min_valid (a minimum count of non-NA
values per window); roll_mean() additionally accepts weights for a weighted
moving average. See the
introductory vignette
and the function reference
for argument details and return-value conventions.
Background
Analysis of time series data often involves "rolling" calculations such as a moving average. These are simple to express in R but slow, so compiled versions of the common functions are valuable. Several R packages already provide some of this functionality:
- zoo — widely used package for ordered observations and rolling calculations
- seismicRoll — rolling functions focused on seismology
- RcppRoll — rolling functions for basic statistics
MazamaRollUtils exists to build up a suite of rolling functions useful in environmental time series analysis, available in a neutral environment with no underlying data model and usable by data analysts at any level of R expertise.
Documentation and Help
Citation
For citation information, use:
citation("MazamaRollUtils")Acknowledgements
This project is supported by the USFS AirFire team.
License
MazamaRollUtils is released under the GPL-3 license.