predict_inspre_G_h5X: Calculates model predictions given new data, with...

In brielin/inspre: INverse SParse REgression

Calculates model predictions given new data, with cross-validation errors.

Description

This function uses the mean((X - XG - ZB)**2) error formulation. TODO: At the moment this pulls all the data into memory which is probably fine since its normally only 10-20 modifying to pull one target at a time to match fit functionality.

Usage

predict_inspre_G_h5X(
  res,
  X,
  X_ntc,
  beta,
  X_targets,
  X_vars,
  vars_to_use = NULL,
  obs_to_use = NULL
)

Arguments

res	Inspre result. Result of running fit_inspre for a single or sequence of hyperparameter values.
X	H5D. Example: ‘X=hfile[[’X']]' where hfile is an hdf5r object containing a data matrix stored under label 'X'.
beta	Sequence of floats. Obsevered scale estimates of instrument effects.
X_targets	Sequence of strings with length equal to number of columns in X. Entries correspond to the target of the instrument applied to that entry.
X_vars	Sequence of strings with length equal to the number of rows in X. Name of the feature measured in that row.
vars_to_use	Sequence of strings. Entries in X_vars to keep. Default NULL to keep all.
obs_to_use	Sequence of bools. Indicator of columns of X to use in calculations. Useful for cross validation. NULL to keep all.

brielin/inspre documentation built on Dec. 3, 2023, 4:55 a.m.