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

## 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

 ```1 2 3 4 5``` ```## 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\$corrected.pval.t))), 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)))`. `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.

## See Also

See also `ITPlmbspline` to fit and test a functional-on-scalar linear model applying the ITP, and `summary.ITPlm` for summaries. See `plot.ITPaov`, `plot.ITP1`, and `plot.ITP2` for the plot method applied to the ITP results of functional analysis of variance, one-population and two-population, respectively.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```# 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 Oct. 30, 2020, 8:15 a.m.