healthyR.ts (version 0.3.1)

ts_growth_rate_vec: Vector Function Time Series Growth Rate

Description

This function computes the growth rate of a numeric vector, typically representing a time series, with optional transformations like scaling, power, and lag differences.

Usage

ts_growth_rate_vec(.x, .scale = 100, .power = 1, .log_diff = FALSE, .lags = 1)

Value

A list object of workflows.

Arguments

.x

A numeric vector

.scale

A numeric value that is used to scale the output

.power

A numeric value that is used to raise the output to a power

.log_diff

A logical value that determines whether the output is a log difference

.lags

An integer that determines the number of lags to use

Author

Steven P. Sanderson II, MPH

Details

The function calculates growth rates for a time series, allowing for scaling, exponentiation, and lag differences. It can be useful for financial data analysis, among other applications.

The growth rate is computed as follows:

• If lags is positive and log_diff is FALSE: growth_rate = (((x / lag(x, lags))^power) - 1) * scale

• If lags is positive and log_diff is TRUE: growth_rate = log(x / lag(x, lags)) * scale

• If lags is negative and log_diff is FALSE: growth_rate = (((x / lead(x, -lags))^power) - 1) * scale

• If lags is negative and log_diff is TRUE: growth_rate = log(x / lead(x, -lags)) * scale

See Also

Other Vector Function: ts_acceleration_vec(), ts_velocity_vec()

Examples

# Calculate the growth rate of a time series without any transformations.
ts_growth_rate_vec(c(100, 110, 120, 130))

# Calculate the growth rate with scaling and a power transformation.
ts_growth_rate_vec(c(100, 110, 120, 130), .scale = 10, .power = 2)

# Calculate the log differences of a time series with lags.
ts_growth_rate_vec(c(100, 110, 120, 130), .log_diff = TRUE, .lags = -1)

# Plot
plot.ts(AirPassengers)
plot.ts(ts_growth_rate_vec(AirPassengers))