Title: | A Goodness-of-Fit Test for Elliptical Distributions with Diagnostic Capabilities |
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Description: | A goodness-of-fit test for elliptical distributions with diagnostic capabilities. Gilles R. Ducharme, Pierre Lafaye de Micheaux (2020) <doi:10.1016/j.jmva.2020.104602>. |
Authors: | Gilles R Ducharme [aut], Pierre Lafaye De Micheaux [aut, cre] |
Maintainer: | Pierre Lafaye De Micheaux <[email protected]> |
License: | GPL (>= 2) |
Version: | 0.5 |
Built: | 2025-02-09 03:28:47 UTC |
Source: | https://github.com/cran/ECGofTestDx |
Smooth tests of goodness-of-fit for multivariate elliptical distributions with diagnostic (Dx) capabilities and
full invariance to affine-linear transformations. By increasing the value of the hyperparameter K
,
the test and the Dx become adaptively consistent against an increasing number of departures from
the null model. The Dx pertains to elements and
of the Cambanis, Huang & Simons
stochastic representation of elliptical data. Note that p-values can be computed via an asymptotic chi-square approximation or by Monte Carlo.
SmoothECTest(data, K = 7, family = "MVN", Est.Choice = "", Cpp = TRUE)
SmoothECTest(data, K = 7, family = "MVN", Est.Choice = "", Cpp = TRUE)
data |
The data set to use. Cases with missing values are removed. |
K |
Integer. Hyperparameter controlling the size of the embedding
family. Should be greater than or equal to 3
for the Multivariate Normal Distribution. The computation time increases
with the size of the data frame and |
family |
The only family available in the current version of the package is the Multivariate Normal Distribution. |
Est.Choice |
Not used yet. Maximum Likelihood Estimation (MLE) or Method of moments. Currently, only the MLE is implemented. |
Cpp |
Logical. If |
List with components:
Q |
The global test statistic with hyperparameter |
dfQ |
Degrees of freedom of the asymptotic chi-square approximation. |
pval.asymp.Q |
Asymptotic p-value for |
Uscaled |
Scaled component |
dfU |
Degrees of freedom of the asymptotic chi-square approximation. |
pval.asymp.U |
Asymptotic p-value for |
Iscaled |
Scaled component |
dfI |
Degrees of freedom of the asymptotic chi-square approximation. |
pval.asymp.I |
Asymptotic p-value for |
Rscaled |
Scaled component |
dfR |
Degrees of freedom of the asymptotic chi-square approximation. |
pval.asymp.R |
Asymptotic p-value for |
G. R. Ducharme, P. Lafaye De Micheaux
Gilles R. Ducharme, Pierre Lafaye de Micheaux (2020). A Goodness-of-fit Test for Elliptical Distributions with Diagnostic Capabilities. Journal of Multivariate Analysis, volume 178.
# The famous (Fisher's or Anderson's) iris data set # Increase the value of K to K = 7 for better results. ressetosa <- SmoothECTest(iris[1:50, -5], K = 3) ressetosa # Examination marks (n = 88) in Vectors, Algebra and Statistics from the "Open # book-Closed book examination" data set (Mardia, Kent and Bibby, 1979, # p. 3-4). # Increase the value of K to K = 5 for better results. data <- scor[, c(2, 3, 5)] result <- SmoothECTest(data, K = 3) result
# The famous (Fisher's or Anderson's) iris data set # Increase the value of K to K = 7 for better results. ressetosa <- SmoothECTest(iris[1:50, -5], K = 3) ressetosa # Examination marks (n = 88) in Vectors, Algebra and Statistics from the "Open # book-Closed book examination" data set (Mardia, Kent and Bibby, 1979, # p. 3-4). # Increase the value of K to K = 5 for better results. data <- scor[, c(2, 3, 5)] result <- SmoothECTest(data, K = 3) result