tsfeatures {tsfeatures} | R Documentation |
Time series feature matrix
Description
tsfeatures
computes a matrix of time series features from a list of time series
Usage
tsfeatures(
tslist,
features = c("frequency", "stl_features", "entropy", "acf_features"),
scale = TRUE,
trim = FALSE,
trim_amount = 0.1,
parallel = FALSE,
multiprocess = future::multisession,
na.action = na.pass,
...
)
Arguments
tslist |
a list of univariate time series, each of class |
features |
a vector of function names which return numeric vectors of features. All features returned by these functions must be named if they return more than one feature. Existing functions from installed packages may be used, but the package must be loaded first. Functions must return a result for all time series, even if it is just NA. |
scale |
if |
trim |
if |
trim_amount |
Default level of trimming if |
parallel |
If TRUE, multiple cores (or multiple sessions) will be used. This only speeds things up when there are a large number of time series. |
multiprocess |
The function from the |
na.action |
A function to handle missing values. Use |
... |
Other arguments get passed to the feature functions. |
Value
A feature matrix (in the form of a tibble) with each row corresponding to one time series from tslist, and each column being a feature.
Author(s)
Rob J Hyndman
Examples
mylist <- list(sunspot.year, WWWusage, AirPassengers, USAccDeaths)
tsfeatures(mylist)