plot.ITPlm: Plotting ITP results for functional-on-scalar linear model...
In alessiapini/fdatest: Interval Wise Testing for Functional Data

plot.ITPlm

R Documentation

Plotting ITP results for functional-on-scalar linear model testing

Description

plot method for class "ITPlm". Plotting function creating a graphical output of the ITP for the test on a functional-on-scalar linear model: functional data, functional coefficients and ITP-adjusted p-values for the F-test and t-tests are plotted.

Usage

## S3 method for class 'ITPlm'
plot(x,xrange=c(0,1),alpha1=0.05,alpha2=0.01,plot.adjpval=FALSE,
                      col=c(1,rainbow(dim(x$adjusted.pval.t)[1])),ylim=range(x$data.eval),
                      ylab='Functional Data',main=NULL,lwd=1,pch=16,
                      ...)

Arguments

`x`	The object to be plotted. An object of class "`ITPlm`", usually, a result of a call to `ITPlmbspline`.
`xrange`	Range of the `x` axis.
`alpha1`	First level of significance used to select and display significant effects. Default is `alpha1 = 0.05`.
`alpha2`	Second level of significance used to select and display significant effects. Default is `alpha1 = 0.01`. `alpha1` and `alpha2` are s.t. `alpha2 < alpha1`. Otherwise the two values are switched.
`plot.adjpval`	A logical indicating wether the plots of adjusted p-values have to be done. Default is `plot.adjpval = FALSE`.
`col`	Vector of colors for the plot of functional data (first element), and functional coefficients (following elements). Default is `col = c(1, rainbow(dim(x$corrected.pval.t)[1]))`.
`ylim`	Range of the `y` axis. Default is `ylim = range(x$data.eval)`.
`ylab`	Label of `y` axis of the plot of functional data. Default is "`Functional Data`".
`main`	An overall title for the plots (it will be pasted to "`Functional Data and F-test`" for the first plot and "`t-test`" for the other plots).
`lwd`	Line width for the plot of functional data. Default is `lwd=16`.
`pch`	Point character for the plot of adjusted p-values. Default is `pch=16`.
`...`	Additional plotting arguments that can be used with function `plot`, such as `graphical parameters` (see `par`).

Value

No value returned. The function produces a graphical output of the ITP results: the plot of the functional data, functional regression coefficients, and ITP-adjusted p-values for the F-test and t-tests. The basis components selected as significant by the tests at level alpha1 and alpha2 are highlighted in the plot of the corrected p-values and in the one of functional data by gray areas (light and dark gray, respectively). The plot of functional data reports the gray areas corresponding to a significant F-test. The plots of functional regression coefficients report the gray areas corresponding to significant t-tests for the corresponding covariate.

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.

Examples

# Importing the NASA temperatures data set
data(NASAtemp)

data <- rbind(NASAtemp$milan,NASAtemp$paris)
lab <- c(rep(0,22),rep(1,22))

# Performing the ITP
ITP.result <- ITPlmbspline(data ~ lab,B=1000,nknots=20,order=3)
# Summary of the ITP results
summary(ITP.result)

# Plot of the ITP results
layout(1)
plot(ITP.result,main='NASA data',xlab='Day',xrange=c(1,365))

# Plots of the adjusted p-values
plot(ITP.result,main='NASA data', plot.adjpval = TRUE,xlab='Day',xrange=c(1,365))

# To have all plots in one device
layout(matrix(1:6,nrow=3,byrow=FALSE))
plot(ITP.result,main='NASA data', plot.adjpval = TRUE,xlab='Day',xrange=c(1,365))

alessiapini/fdatest documentation built on April 28, 2024, 12:35 a.m.