dplyr, knitr, magrittr, rmarkdown, spelling, testthat

person("Dawid", "Kałędkowski",
email = "dawid.kaledkowski@gmail.com",
comment = c(ORCID = "0000-0001-9533-457X"),
role = c("aut", "cre"))
Calculates running functions  with varying window size and missing
handling options. Package brings also running streak and running which, what
extends beyond range of functions already implemented in R packages. Calculating
on windows depending on date also available.
Dawid Kałędkowski [aut, cre] (<https://orcid.org/0000-0001-9533-457X>)

Fully supports rolling windows operations by controlling window length,
window lag, time indexing. With runner one can apply any R function on rolling
windows. Package eases work with equally and unequally spaced time series.

Lightweight library for rolling windows operations. Package enables
full control over the window length, window lag and a time indices. With a runner
one can apply any R function on a rolling windows. The package eases work with
equally and unequally spaced time series.

Package 'runonce' helps automating the saving of long-running code
to help running the same code multiple times. If you run some long-running
code once, it saves the result in a file on disk. Then, if the result
already exists, i.e. if the code has already been run and its output has
already been saved, it just read the result from the stored file instead
of running the code again.

person("Florian", "Privé",
role = c("aut", "cre"),
email = "florian.prive.21@gmail.com")
Package 'runonce' helps automating the saving of long-running code
to help running the same code multiple times. If you run some long-running
code once, it saves the result in a file on disk. Then, if the result
already exists, i.e. if the code has already been run and its output has
already been saved, it just reads the result from the stored file instead
of running the code again.

Fast Computation of Running Statistics for Time Series
c(
person("Marta", "Karas", email = "marta.karass@gmail.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-5889-3970")),
person("Jacek", "Urbanek", role = c("aut"),
comment = c(ORCID = "0000-0002-1890-8899")),
person("John", "Muschelli", role = c("ctb"),
comment = c(ORCID = "0000-0001-6469-1750"))
)
Provides methods for fast computation of running sample
statistics for time series. These include: (1) mean, (2)
standard deviation, and (3) variance over a fixed-length window
of time-series, (4) correlation, (5) covariance, and (6)
Euclidean distance (L2 norm) between short-time pattern and
time-series. Implemented methods utilize Convolution Theorem to
compute convolutions via Fast Fourier Transform (FFT).
covr, testthat, ggplot2, knitr, rmarkdown, sessioninfo,
rbenchmark, cowplot, spelling