get_trends {COINr}

Get time trends

Description

Get time trends from a purse object. This function extracts a panel data set from a purse, and calculates trends for each indicator/unit pair using a specified function f_trend. For example, if f_trend = "CAGR", this extracts the time series for each indicator/unit pair and passes it to CAGR().

Usage

get_trends(
  purse,
  dset,
  uCodes = NULL,
  iCodes = NULL,
  Time = NULL,
  use_latest = NULL,
  f_trend = "CAGR",
  interp_at = NULL,
  adjust_directions = FALSE
)

Arguments

purse

A purse object

dset

Name of the data set to extract, passed to get_data.purse()

uCodes

Optional subset of unit codes to extract, passed to get_data.purse()

iCodes

Optional subset of indicator/aggregate codes to extract, passed to get_data.purse()

Time

Optional vector of time points to extract, passed to get_data.purse()

use_latest

A positive integer which specifies to use only the latest "n" data points. If this is specified, it overrides Time. If e.g. use_latest = 5, will use the latest five observations, working backwards from the latest non-NA point.

f_trend

Function that returns a metric describing the trend of the time series. See details.

interp_at

Option to linearly interpolate missing data points in each time series. Must be specified as a vector of time values where to apply interpolation. If interp_at = "all", will attempt to interpolate at every time point. Uses linear interpolation - note that any NAs outside of the range of observed values will not be estimated, i.e. this does not extrapolate beyond the range of data. See approx_df().

adjust_directions

Logical: if TRUE, trend metrics are adjusted according to indicator/aggregate directions input in iMeta (i.e. if the corresponding direction is -1, the metric will be multiplied by -1).

Details

This function requires a purse object as an input. The data set is selected using get_data(), such that a subset of the data set can be analysed using the uCodes, iCodes and Time arguments. The latter is useful especially if only a subset of the time series should be analysed.

The function f_trend is a function that, given a time series, returns a trend metric. This must follow a specific format. It must of course be available to call, and must have arguments y and x, which are respectively a vector of values and a vector indexing the values in time. See prc_change() and CAGR() for examples. The function must return a single value (not a vector with multiple entries, or a list). The function can return either numeric or character values.

Value

A data frame in long format, with trend metrics for each indicator/unit pair, plus data availability statistics.

Examples

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