This repository contains an R package called trendr, which fits a locally-linear state-space model (LLM-SSM) to time series data. trendr has been used on a number of research projects at the Data Science Campus, Office for National Statistics including pygrams.

Software Prerequisites

  • R and your GUI of choice, such as RStudio

Data Prerequisites

All time series data must be loaded into R as a data frame comprising at least two columns:

  • A sequential numeric column 1, 2, 3... or sequential datetime column 01/01/2020, 02/01/2020, 3/01/2020...
  • A value column 43, 55, 76...

The data must be equally spaced (daily) with no missing values. The CSV file must contain headers, the header names can be specified in trendr() using the value.colname and time.colname parameters.

Using RStudio

As with any R package, it can be loaded in an R session using:

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# R
library(trendr)

Then you can use the trendr function:

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# R
trendr(
  df,
  value.colname,
  time.colname,
  output.dir,
  output.file,
  output.plot
)

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