cosinor: Trigonometric basis expansion

In LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

Trigonometric basis expansion

Description

Builds a design matrix of sin/cos pairs for use in models with periodic predictors. Can be used directly or inside formulas passed to make_matrices (where expansion is handled automatically).

Usage

cosinor(x, period = 24)

Arguments

x	Numeric vector of the periodic variable.
period	Numeric vector of period lengths, e.g. 24 for a daily cycle with hourly data or c(24, 12) for a daily + semi-daily cycle.

Details

The resulting columns form the basis for linear predictors of the form

\eta_t = \beta_0 + \sum_k \Bigl( \beta_{1k} \sin\!\Bigl(\tfrac{2 \pi x_t}{\text{period}_k}\Bigr) + \beta_{2k} \cos\!\Bigl(\tfrac{2 \pi x_t}{\text{period}_k}\Bigr) \Bigr).

Value

A numeric matrix with 2 * length(period) columns named sin(2*pi*x/period) / cos(2*pi*x/period).

Examples

cosinor(1:24, period = 24)
cosinor(1:24, period = c(24, 12, 6))

## In model formulas (expand_cosinor handles the expansion):
form <- ~ x + temp * cosinor(hour, c(24, 12))
data <- data.frame(x = runif(24), temp = rnorm(24, 20), hour = 1:24)
modmat <- make_matrices(form, data = data)

LaMa documentation built on July 25, 2026, 1:08 a.m.