Prediction for a Single Subject

This loops over all timepoints for a single subject and makes predictions by comparing the number of timepoints in @interventions and in @values. The gap will be filled in one step at a time using mbtransfer_predict_step().

Usage

model_predict_single(fit, ts_inter, lags, subject = NULL, interactions = NULL)

Arguments

fit

An object of class mbtransfer_model, as generated using the mbtransfer function. This includes trained boosting models for every taxon, stored within the @parameters slot.

ts_inter

A new ts_inter_single object over which to perform prediction. This method will make predictions for every timepoint that appears in the @interventions slot but not the @values. This is assumed to be a single subject from a larger ts_inter object.

lags

A vector specifying P and Q in the trained mbtransfer model.

subject

A static data frame of subject-level variables. This will be concatenated to time-varying intervention and taxonomic covariates when making predictions. This is analogous to the training process.