# One population Interval Testing Procedure with B-spline basis

### Description

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.

### Usage

1 | ```
ITP1bspline(data, mu = 0, order = 2, nknots = dim(data)[2], B = 10000)
``` |

### Arguments

`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 |

### Value

`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). |

### 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.

### See Also

See also `ITP1fourier`

, `ITP2bspline`

, `ITP2fourier`

, `ITP2pafourier`

, and `ITPimage`

.

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
# 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)
``` |