astsa — applied statistical time series analysis

    ASTSA ...

… more than just data … it’s also a palindrome


astsa includes data sets and scripts for analyzing time series in both the frequency and time domains including state space modeling as well as supporting the Springer text, Time Series Analysis and Its Applications: With R Examples and the Chapman & Hall text Time Series: A Data Analysis Approach using R. Most scripts are designed to require minimal input to produce aesthetically pleasing output for ease of use in live demonstrations and course work.

We do not always push the latest version of the package to CRAN, but the latest working version of the package will always be at Github.


WARNING: If loaded, the package dplyr may (and probably will) corrupt the base scripts filter and lag that a time series analyst uses often. An easy fix if you’re analyzing time series (or teaching a class) is to (tell students to) do the following if dplyr is going being used:

# [1] either detach it if it's loaded but no longer needed
detach(package:dplyr)  

# [2] or fix it yourself when loading dplyr 
# this is a great idea from https://stackoverflow.com/a/65186251
library(dplyr, exclude = c("filter", "lag"))   # remove the culprits
dlag    = dplyr::lag                           # then correct ... 
dfilter = dplyr::filter                        # ... the blunders
#  Now use `dlag` and `dfilter` in dplyr scripts and
# `lag` and `filter` can be use as originally intended

# [3] or just take back the commands
filter = stats::filter
lag    = stats::lag
# in this case, you can still use these for dplyr
dlag    = dplyr::lag     
dfilter = dplyr::filter