prc_change: Percentage change of time series

In COINr: Composite Indicator Construction and Analysis

Percentage change of time series

Description

Calculates the percentage change in a time series from the initial value. The time series is defined by y the response variable, indexed by x, the time variable. The per argument can optionally be used to scale the result according to a period of time. E.g. if the units of x are years, setting x = 10 will measure the percentage change per decade.

Usage

prc_change(y, x, per = 1)

Arguments

y	A numeric vector
x	A numeric vector of the same length as y, indexing y in time. No NA values are allowed in x.
per	Numeric value to scale the change according to a period of time. See description.

Details

This function operates in two ways, depending on the number of data points. If x and y have two non-NA observations, percentage change is calculated using the first and last values. If three or more points are available, a linear regression is used to estimate the average percentage change. If fewer than two points are available, the percentage change cannot be estimated and NA is returned.

If all y values are equal, it will return a change of zero.

Value

Percentage change as a scalar value.

Examples

# a time vector
x <- 2011:2020

# some random points
y <- runif(10)

# find percentage change per decade
prc_change(y, x, 10)

COINr documentation built on Oct. 9, 2023, 5:07 p.m.