Package index • trendseries

Trend extraction

Add or extract smooth trend components.

augment_trends(): Add trend columns to data frame
extract_trends(): Extract trends from time series objects
detrend_series(): Detrend a time series

Rolling aggregations

Calculate rolling and year-to-date statistics.

augment_rolling(): Add rolling aggregation columns to a data frame
roll_series(): Rolling aggregations for time series objects

Indexing

Rescale series to a common reference value.

index_series(): Index one or more series

Decomposition

Split a series into trend, seasonal, and remainder components.

decompose_series(): Decompose time series into trend, seasonal, and remainder components
deseason_series(): Seasonally adjust (deseason) a time series

Converters

Convert between data frames and time series objects.

converters: Data Format Conversion Utilities
df_to_ts(): Convert a data.frame into a time series (ts)
ts_to_df(): Convert time series to tibble

Datasets

Bundled economic time series for examples and testing.

coffee_arabica: Daily Arabica Coffee Price Indicator
coffee_robusta: Daily Robusta Coffee Price Indicator
electric: Residential Electricity Consumption
electricity: Electricity Consumption by Sector
gdp_construction: Quarterly GDP — Building Industry
ibcbr: Central Bank Economic Activity Index (IBC-Br)
metadata_series: Series Metadata
oil_derivatives: Petroleum Derivatives Production
retail_autofuel: Great Britain Retail Sales Volume Index: Automotive Fuel
retail_volume: Great Britain Retail Sales Volume Indices
transit_london_avgs: TfL Network Demand: Average Daily Journeys
transit_london_monthly: TfL Network Demand: Monthly Bus and Tube Journeys
vehicles: Total Vehicle Sales