README.md

In MazamaRollUtils: Efficient Rolling Functions

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

• Package website
• Introduction to MazamaRollUtils
• Function reference
• GitHub Issues
• GitHub Discussions

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.

MazamaRollUtils documentation built on Sept. 1, 2026, 5:09 p.m.