README

The R package gratis (previously known as tsgeneration) provides efficient algorithms for generating time series with diverse and controllable characteristics.

Installation

CRAN version

install.packages("gratis")

Development version

You can install the development version of gratis package from GitHub Repository with:

devtools::install_github("ykang/gratis")

Usage

Tutorial video

Load the package

library(gratis)
library(feasts)

Generate diverse time series

set.seed(27)
mar_model(seasonal_periods=12) %>%
  generate(length=120, nseries=2) %>%
  autoplot(value)

Generate mutiple seasonal time series

mar_model(seasonal_periods=c(24, 24*7)) %>%
  generate(length=24*7*10, nseries=12) %>%
  autoplot(value)

Generate time series with controllable features

library(dplyr)
# Function to return spectral entropy, and ACF at lags 1 and 2
# given a numeric vector input
my_features <- function(y) {
  c(tsfeatures::entropy(y), acf = acf(y, plot = FALSE)$acf[2:3, 1, 1])
}
# Produce series with entropy = 0.5, ACF1 = 0.9 and ACF2 = 0.8
df <- generate_target(
  length = 60, feature_function = my_features, target = c(0.5, 0.9, 0.8)
)
df %>%
 as_tibble() %>%
 group_by(key) %>%
 reframe(value = my_features(value), 
           feature=c("entropy","acf1", "acf2")
           )
#> # A tibble: 30 × 3
#>    key       value feature
#>    <chr>     <dbl> <chr>  
#>  1 Series 1  0.509 entropy
#>  2 Series 1  0.906 acf1   
#>  3 Series 1  0.787 acf2   
#>  4 Series 10 0.465 entropy
#>  5 Series 10 0.896 acf1   
#>  6 Series 10 0.775 acf2   
#>  7 Series 2  0.483 entropy
#>  8 Series 2  0.901 acf1   
#>  9 Series 2  0.812 acf2   
#> 10 Series 3  0.504 entropy
#> # ℹ 20 more rows
autoplot(df)

Web application

app_gratis()

gratis