predict.ngme: Prediction.

In davidbolin/ngme: Linear Mixed Effects Models With Flexible Distributions

Prediction.

Description

Obtains predicted values based on filtering and smoothing distributions.

Usage

## S3 method for class 'ngme'
predict(
  object,
  newdata = NULL,
  id = NULL,
  type = "Filter",
  quantiles = c(0.025, 0.975),
  controls = list(return.samples = FALSE, predict.derivatives = NULL, excursions =
    NULL, crps = TRUE, crps.skip = 1, nSim = 1000, nBurnin = 100, silent = TRUE, n.cores
    = 1, batch.size = 100)
)

Arguments

object	A fitted object obtained by calling "ngme".
id	A numeric vector containing the ID's of the subjects for whom predictions are to be obtained. Default is set to "NULL" indicating perform predictions for all the subjects.
type	A character string for the type of prediction: "Nowcast" for nowcasting, "Filter" for one step-ahead forecasting, "Smoothing" for smoothing.
quantiles	A two-element vector that contains the quantiles of the predictions to be calculated.
controls	A list of control variables. "return.samples" A logical variable for returning the Monte Carlo samples used to compute the predictions; "TRUE" indicates return, "FALSE" do not return. "predict.derivatives" A list for calculating excursion probabilities Bfixed A list of fixed effects covariate matrices at t_{ij} + delta. Brandom A list of random effects covariate matrices at t_{ij}+ delta. delta A numeric value indicating \Deltat for calculating the derivative numerically. "excursions" A list of excursion probabilities to compute. Each list should contain: "type" Type of excursion for indicating calculation of the probabilities, greater than or less than a threshol. User should specify "greater than" by ">" "less than" by "<". "level" A numeric value for the threshold compute excursion probability for. "process" A character string that for which component of the model the excursion probabilities to be calculated. x\alpha + dU + W + Z with x \alpha being fixed effects, dU random effects and Z noise, to compute the probability for. 'X' for x\alpha + dU + W, 'W' for W, 'Y' for x\alpha + dU + W + Z, 'Xderivative' for the first derivarive of x\alpha + dU + W, and 'Wderivative' for the first derivariate of W. "crps" A logical variable for calculating continuous ranked probability score (CRPS); "TRUE" indicates calculate, "FALSE" do not calculate. "crps.skip" A numerical value, say a, that indicates every ath element of the sample to be used to compute the crps score. "nSim" A numerical value for the number of samples for the Gibbs sampler to obtain the predictions. "nBurnin" A numeric value for the number of samples that are discarded as burn-in whilst calculating the predictions. silent A logical value for printing the details; "TRUE" indicates do not print, "FALSE" indicates print. n.cores Number of cores to use for paralell computations, default is set to 1. batch.size Number of subjects to include in each paralell batch.

Value

A list of output.

See Also

ngme

Examples

  ## Not run: 
  fit <- ngme(...)
  predict(fit, ...)
  
## End(Not run)

davidbolin/ngme documentation built on Dec. 5, 2023, 11:48 p.m.