summarise_stats: Summarise distributional statistics by time series

In tscv: Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation

Summarise distributional statistics by time series

Description

Calculate descriptive statistics for one or more time series.

Usage

summarise_stats(.data, context)

Arguments

.data	A tibble in long format containing time series data.
context	A named list with the identifiers for series_id, value_id, and index_id.

Details

summarise_stats() groups the input data by the series identifier supplied in context and returns one row per time series.

The function reports:

• mean: arithmetic mean;

• median: median;

• mode: kernel-density based mode estimate;

• sd: standard deviation;

• p0: minimum;

• p25: 25 percent quantile;

• p75: 75 percent quantile;

• p100: maximum;

• skewness: moment-based skewness;

• kurtosis: moment-based kurtosis.

Missing values are removed when calculating the statistics.

Value

A tibble containing one row per time series and the calculated descriptive statistics.

See Also

Other data analysis: acf_vec(), estimate_acf(), estimate_kurtosis(), estimate_mode(), estimate_pacf(), estimate_skewness(), pacf_vec(), summarise_data(), summarise_split()

Examples

library(dplyr)

context <- list(
  series_id = "series",
  value_id = "value",
  index_id = "index"
)

data <- M4_monthly_data |>
  filter(series %in% c("M23100", "M14395"))

summarise_stats(
  .data = data,
  context = context
)

tscv documentation built on May 13, 2026, 9:07 a.m.