summary.ITPlm: Summarizing Functional-on-Scalar Linear Model Fits

In fdatest: Interval Testing Procedure for Functional Data

Summarizing Functional-on-Scalar Linear Model Fits

Description

summary method for class "ITPlm".

Usage

## S3 method for class 'ITPlm'
summary(object, ...)

Arguments

object	An object of class "ITPlm", usually, a result of a call to ITPlmbspline.
...	Further arguments passed to or from other methods.

Value

The function summary.ITPlm computes and returns a list of summary statistics of the fitted functional-on-scalar linear model given in object, using the component "call" from its arguments, plus:

ttest	A L+1 x 1 matrix with columns for the functional regression coefficients, and corresponding (two-sided) ITP-adjusted minimum p-values of t-tests (i.e., the minimum p-value over all p basis components used to describe functional data).
R2	Range of the functional R-squared.
ftest	ITP-adjusted minimum p-value of functional F-test.

Author(s)

Alessia Pini, Simone Vantini

References

A. Pini and S. Vantini (2013). The Interval Testing Procedure: Inference for Functional Data Controlling the Family Wise Error Rate on Intervals. MOX-report 13/2013, Politecnico di Milano.

K. Abramowicz, S. De Luna, C. Häger, A. Pini, L. Schelin, and S. Vantini (2015). Distribution-Free Interval-Wise Inference for Functional-on-Scalar Linear Models. MOX-report 3/2015, Politecnico di Milano.

See Also

See ITPlmbspline for fitting and testing the functional linear model and plot.ITPlm for plots. See also ITPaovbspline, ITP1bspline, ITP2bspline, ITP2fourier, ITP2pafourier.

Examples

# Importing the NASA temperatures data set
data(NASAtemp)

temperature <- rbind(NASAtemp$milan,NASAtemp$paris)
groups <- c(rep(0,22),rep(1,22))

# Performing the ITP
ITP.result <- ITPlmbspline(temperature ~ groups, B=1000,nknots=20)

# Summary of the ITP results
summary(ITP.result)

fdatest documentation built on May 4, 2022, 9:06 a.m.