fanova.onefactor: One-way anova model for functional data

In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

One–way anova model for functional data

Description

One–way anova model for k independent samples of functional data. The function contrasts the null hypothesis of equality of mean functions of functional data based on the an asymptotic version of the anova F–test.

H_0: m_1=,…=m_k,

Usage

fanova.onefactor(
  object,
  group,
  nboot = 100,
  plot = FALSE,
  verbose = FALSE,
  ...
)

Arguments

object	functional response data. fdata class object with n curves.
group	a factor specifying the class for each curve.
nboot	number of bootstrap samples.
plot	if TRUE, plot the mean of each factor level and the results of test.
verbose	if TRUE, print intermediate results.
...	further arguments passed to or from other methods.

Details

The function returns the p–value of test using one–way anova model over nboot runs.

Value

Returns:

• p-value probability of rejecting the null hypothesis H0 at a significance level

• stat statistic value of test.

• wm statistic values of bootstrap resamples.

Note

anova.onefactor deprecated.

Author(s)

Juan A. Cuesta-Albertos, Manuel Febrero-Bande, Manuel Oviedo de la Fuente
[e-mail]

References

Cuevas, A., Febrero, M., & Fraiman, R. (2004). An anova test for functional data. Computational statistics & data analysis, 47(1), 111-122.

See Also

See Also as: fanova.RPm

Examples

## Not run: 
data(MCO)
grupo<-MCO$classintact
datos<-MCO$intact
res=fanova.onefactor(datos,grupo,nboot=50,plot=TRUE)
grupo <- MCO$classpermea
datos <- MCO$permea
res=fanova.onefactor(datos,grupo,nboot=50,plot=TRUE)

## End(Not run)  

fda.usc documentation built on Oct. 17, 2022, 9:06 a.m.