ITP1bspline | R Documentation |
The function implements the Interval Testing Procedure for testing the center of symmetry of a functional population evaluated on a uniform grid. Data are represented by means of the B-spline expansion and the significance of each basis coefficient is tested with an interval-wise control of the Family Wise Error Rate. The default parameters of the basis expansion lead to the piece-wise interpolating function.
ITP1bspline(data, mu = 0, order = 2, nknots = dim(data)[2], B = 10000)
data |
Pointwise evaluations of the functional data set on a uniform grid. |
mu |
The center of symmetry under the null hypothesis: either a constant (in this case, a constant function is used) or a |
order |
Order of the B-spline basis expansion. The default is |
nknots |
Number of knots of the B-spline basis expansion. The default is |
B |
The number of iterations of the MC algorithm to evaluate the p-values of the permutation tests. The defualt is |
ITP1bspline
returns an object of class
"ITP1
".
An object of class "ITP1
" is a list containing at least the following components:
basis |
String vector indicating the basis used for the first phase of the algorithm. In this case equal to |
test |
String vector indicating the type of test performed. In this case equal to |
mu |
Center of symmetry under the null hypothesis (as entered by the user). |
coeff |
Matrix of dimensions |
pval |
Uncorrected p-values for each basis coefficient. |
pval.matrix |
Matrix of dimensions |
corrected.pval |
Corrected p-values for each basis coefficient. |
labels |
Labels indicating the population membership of each data (in this case always equal to |
data.eval |
Evaluation on a fine uniform grid of the functional data obtained through the basis expansion. |
heatmap.matrix |
Heatmap matrix of p-values (used only for plots). |
Alessia Pini, Simone Vantini
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.
See also ITP1fourier
, ITP2bspline
, ITP2fourier
, ITP2pafourier
, and ITPimage
.
# Importing the NASA temperatures data set data(NASAtemp) # Performing the ITP for two populations with the B-spline basis ITP.result <- ITP1bspline(NASAtemp$paris,mu=4,nknots=50,B=1000) # Plotting the results of the ITP plot(ITP.result,xrange=c(0,12),main='Paris temperatures') # Plotting the p-value heatmap ITPimage(ITP.result,abscissa.range=c(0,12)) # Selecting the significant components for the radius at 5% level which(ITP.result$corrected.pval < 0.05)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.