Vector Function Time Series Growth Rate

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)

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

Value

A list object of workflows.

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

Author

Steven P. Sanderson II, MPH

Examples

# Calculate the growth rate of a time series without any transformations.
ts_growth_rate_vec(c(100, 110, 120, 130))
#> [1]        NA 10.000000  9.090909  8.333333
#> attr(,"name")
#> [1] "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)
#> [1]       NA 2.100000 1.900826 1.736111
#> attr(,"name")
#> [1] "c(100, 110, 120, 130)"

# Calculate the log differences of a time series with lags.
ts_growth_rate_vec(c(100, 110, 120, 130), .log_diff = TRUE, .lags = -1)
#> [1] -9.531018 -8.701138 -8.004271        NA
#> attr(,"name")
#> [1] "c(100, 110, 120, 130)"

# Plot
plot.ts(AirPassengers)

plot.ts(ts_growth_rate_vec(AirPassengers))