predict.fcr: Prediction for fcr

In fcr: Functional Concurrent Regression for Sparse Data

Description

Predict method for fcr

Usage

## S3 method for class 'fcr'
predict(object, newdata, type = "link", ...)

Arguments

object	object of class fcr.
newdata	data frame including all predictors used in the model fitting procedure. missing values for the responses are OK. Missing covariate values will result in pairwise deletion with a warning message.
type	defaults to link (i.e. response). See predict.gam for additional information.
...	additional arguments to be passed to predict.gam

Value

An object containing two elements

dynamic_predictions

Predictions corresponding to dynamic predictions (i.e. subject ids not included in the original fitting). Note that these predictions are slower and do not incorporate the estimated covariance between random effects and fixed effects in making predictions. This is different than the in sample predictions which account for this estimated covariance. See predict.gam for more information.

• fitted.values

  • y.pred fitted \hat{y}

  • se.fit standard errors used to create confidence intervals for \hat{y}, √{var(y)}

  • se.fit.p standard errors used for creating prediction intervals for \hat{y}, √{var(y) + \hat{σ^2}}

  • random subject specific random effects b_i

• scores matrix of BLUPs for subjects' eigenscores

• data newdata supplied to the function

insample_predictions

Predictions for subject ids included in the original fitting. This returns all output from the relevant predict.gam/predict.bam call.

Examples

## see examples in fcr

fcr documentation built on May 1, 2019, 8:26 p.m.