A Consistent Test for Multivariate Normality Based on the Empirical Characteristic Function.
A Geometric Appraoch to Finite Sample and Large Deviation Properties in Two-Way ANOVA with Spherically Distributed Error Vectors.
A homogeneity test of large dimensional covariance matrices under non-normality
A test statistic for homogeneity of two or more covariance matrices is presented when the distributions may be non-normal and the dimension may exceed the sample size. Using the Frobenius norm of the difference of null and alternative hypotheses, the statistic is constructed as a linear combination of consistent, location-invariant, estimators of trace functions that constitute the norm. These estimators are defined as -statistics and the corresponding theory is exploited to derive the normal limit...
A one-way ANOVA test for functional data with graphical interpretation
A new functional ANOVA test, with a graphical interpretation of the result, is presented. The test is an extension of the global envelope test introduced by Myllymäki et al. (2017, Global envelope tests for spatial processes, J. R. Statist. Soc. B 79, 381-404, doi: 10.1111/rssb.12172). The graphical interpretation is realized by a global envelope which is drawn jointly for all samples of functions. If a mean function computed from the empirical data is out of the given envelope, the null hypothesis...
ABSTRACT - Some Tests on Exponential Populations.
Algorithm 33. Test for difference in trends in a two-factor experiment with repeated measurements
Algorithm 34. Use of orthogonal components in tests for trend
Algorithms for determining the model structure of a controlled system
Analysis of variance as regression model with a reparametrization restriction
Let us consider the linear model covering the one-way classification as a special casse. In the paper the relationship between testing of some linear hypothesis and estimating of parameters in the linear model by common software packages is examined.
Au-delà de l'analyse de la variance ?
Canonic inference and commutative orthogonal block structure
It is shown how to define the canonic formulation for orthogonal models associated to commutative Jordan algebras. This canonic formulation is then used to carry out inference. The case of models with commutative orthogonal block structures is stressed out.
Choosing the best -divergence goodness-of-fit statistic in multinomial sampling with linear constraints
In this paper we present a simulation study to analyze the behavior of the -divergence test statistics in the problem of goodness-of-fit for loglinear models with linear constraints and multinomial sampling. We pay special attention to the Rényi’s and -divergence measures.
Classification into two von Mises distributions with unknown mean directions
The paper deals with two Mises distributions on the circle with unknown mean directions and a common concentration parameter that is known. The likelihood rule and the plug-in rule are examined. For the statistic of the plug-in rule, the moment generating function is given and a method of obtaining the moments is proposed.
Classifications with relations. II. Asymptotic testing and estimation
Classifiers for doubly multivariate data
This paper proposes new classifiers under the assumption of multivariate normality for multivariate repeated measures data (doubly multivariate data) with Kronecker product covariance structures. These classifiers are especially useful when the number of observations is not large enough to estimate the covariance matrices, and thus the traditional classifiers fail. The quality of these new classifiers is examined on some real data. Computational schemes for maximum likelihood estimates of required...
Coefficient de corrélation et prise de décision
Conditions for Invariance of the Multivariate Versions of Grubb's Test and Bartlett's Test. Under a General Dependency Structure.
Consistency of Some Tests for Multivariate Normality.
Contrastación de hipótesis en diseños multivariados split-plot con matrices de dispersión arbitrarias.
El presente trabajo examina diversos procedimientos para contrastar hipótesis nulas globales, correspondientes a datos obtenidos mediante diseños multivariados split-plot cuando se incumple el supuesto de homogeneidad de las matrices de dispersión. Un examen de estos procedimientos para un amplio número de variables confirma, por un lado, la robustez del procedimiento multivariado de Welch-James dado por Johansen (1980) para probar el efecto principal de los ensayos y, por otro, la robustez de la...
Detecting Changes in a Multivariate Renewal Process.