forecast.lfq_fit: Forecast lineage frequencies

In lineagefreq: Lineage Frequency Dynamics from Genomic Surveillance Counts

Forecast lineage frequencies

Description

Projects lineage frequencies forward in time using the fitted model. Prediction uncertainty is quantified by parametric simulation from the estimated parameter distribution.

Usage

## S3 method for class 'lfq_fit'
forecast(
  object,
  horizon = 28L,
  ci_level = 0.95,
  n_sim = 1000L,
  sampling_noise = TRUE,
  effective_n = 100L,
  ...
)

Arguments

object	An lfq_fit object.
horizon	Number of days to forecast. Default 28 (4 weeks).
ci_level	Confidence level for prediction intervals. Default 0.95.
n_sim	Number of parameter draws for prediction intervals. Default 1000.
sampling_noise	Logical; add multinomial sampling noise to prediction intervals? Default TRUE. When TRUE, each draw includes both parameter uncertainty (from the MLE covariance) and observation-level multinomial sampling variability.
effective_n	Effective sample size for multinomial sampling noise. Default 100, corresponding to a typical weekly sequencing volume per reporting unit. Smaller values produce wider (more conservative) prediction intervals.
...	Unused.

Value

An lfq_forecast object (tibble subclass) with columns:

.date

Date.

.lineage

Lineage name.

.median

Median predicted frequency.

.lower

Lower prediction bound.

.upper

Upper prediction bound.

.type

"fitted" or "forecast".

Examples

sim <- simulate_dynamics(n_lineages = 3,
  advantages = c("A" = 1.2, "B" = 0.8), seed = 1)
fit <- fit_model(sim, engine = "mlr")
fc <- forecast(fit, horizon = 21)
fc

lineagefreq documentation built on April 3, 2026, 9:09 a.m.