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().
get_trends(
purse,
dset,
uCodes = NULL,
iCodes = NULL,
Time = NULL,
use_latest = NULL,
f_trend = "CAGR",
interp_at = NULL,
adjust_directions = FALSE
)A data frame in long format, with trend metrics for each indicator/unit pair, plus data availability statistics.
A purse object
Name of the data set to extract, passed to get_data.purse()
Optional subset of unit codes to extract, passed to get_data.purse()
Optional subset of indicator/aggregate codes to extract, passed to get_data.purse()
Optional vector of time points to extract, passed to get_data.purse()
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.
Function that returns a metric describing the trend of the time series. See details.
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().
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).
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.