BNPR_forecast: Forecast using Bayesian Nonparametric phylodynamics
In Mamie/PILAF: PILAF: Phylodynamics InfLuenzA Forecast

Forecast using Bayesian Nonparametric phylodynamics

BNPR_forecast(data, last_time, formula, lengthout = 100, pref = FALSE,
  prec_alpha = 0.01, prec_beta = 0.01, beta1_prec = 0.001,
  fns = NULL, log_fns = TRUE, simplify = TRUE, derivative = FALSE,
  forward = TRUE, pred = 4)

`data`	An ape phylo object
`last_time`	The time of last sampling point
`formula`	INLA formula to model Ne (y) with respect to time and week
`lengthout`	numeric specifying number of grid points.
`pref`	logical. Should the preferential sampling model be used?
`prec_alpha`	numerics specifying gamma prior for precision κ.
`prec_beta`	numerics specifying gamma prior for precision κ.
`beta1_prec`	numeric specifying precision for normal prior on β_1.
`fns`	list containing functions of covariates.
`log_fns`	logical whether or not to to apply a log-transformation to the output of the functions in `fns`.
`simplify`	logical whether to fully bucket all Poisson points.
`derivative`	logical whether to calculate estimates of the log-derivative.
`forward`	logical whether to use the finite difference approximations of the log-derivative as a forward or backward derivative.