# ITPimage: Heatmap plot of the Interval Testing Procedure results In alessiapini/fdatest: Interval Wise Testing for Functional Data

## Description

Plotting function creating a graphical output of the ITP: the p-value heat-map, the plot of the corrected p-values, and the plot of the functional data.

## Usage

 `1` ```ITPimage(ITP.result, alpha = 0.05, abscissa.range = c(0, 1), nlevel = 20) ```

## Arguments

 `ITP.result` Results of the ITP, as created by `ITP1bspline`, `ITP1fourier`, `ITP2bspline`, `ITP2fourier`, and `ITP2pafourier`. `alpha` Threshold for the interval-wise error rate used for the hypothesis test. The default is `alpha`=0.05. `abscissa.range` Range of the plot abscissa. The default is `c(0,1)`. `nlevel` Number of desired color levels for the p-value heatmap. The default is `nlevel=20`.

## References

A. Pini and S. Vantini (2017). The Interval Testing Procedure: Inference for Functional Data Controlling the Family Wise Error Rate on Intervals. Biometrics 73(3): 835–845.

See `plot.ITP1`, `plot.ITP2`, `plot.ITPlm`, and `plot.ITPaov` for the plot method applied to the ITP results of one- and two-population tests, linear models, and ANOVA, respectively. See also `ITP1bspline`, `ITP1fourier`, `ITP2bspline`, `ITP2fourier`, and `ITP2pafourier` for applying the ITP.
 ``` 1 2 3 4 5 6 7 8 9 10``` ```# Importing the NASA temperatures data set data(NASAtemp) # Performing the ITP for two populations with the B-spline basis ITP.result <- ITP2bspline(NASAtemp\$milan,NASAtemp\$paris,nknots=20,B=1000) # Plotting the results of the ITP ITPimage(ITP.result,abscissa.range=c(0,12)) # Selecting the significant components for the radius at 5% level which(ITP.result\$corrected.pval < 0.05) ```