Generalized F-tests for the multivariate normal mean

نویسندگان

  • Jiajuan Liang
  • Man-Lai Tang
چکیده

Based on Läuter’s (Biometrics, 1996) exact t test for biometrical studies related to the multivariate normal mean, we develop a generalized F -test for the multivariate normal mean and extend it to multiple comparison. The proposed generalized F tests have simple approximate null distributions. A Monte Carlo study and two real examples show that the generalized F -test is at least as good as the optional individual Läuter’s test and can improve its performance in some situations where the projection directions for the Läuter’s test may not be suitably chosen. It is discussed that the generalized F -test could be superior to individual Läuter’s tests and the classical Hotelling T 2-test for the general purpose of testing the multivariate normal mean. It is shown by Monte Carlo studies that the extended generalized F test outperforms the commonly-used classical test for multiple comparison of normal means in the case of high dimension with small sample sizes. AMS Classification: 62F03; 62F05

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparing Mean Vectors Via Generalized Inference in Multivariate Log-Normal Distributions

Abstract In this paper, we consider the problem of means in several multivariate log-normal distributions and propose a useful method called as generalized variable method. Simulation studies show that suggested method has a appropriate size and power regardless sample size. To evaluation this method, we compare this method with traditional MANOVA such that the actual sizes of the two methods ...

متن کامل

Invariant Empirical Bayes Confidence Interval for Mean Vector of Normal Distribution and its Generalization for Exponential Family

Based on a given Bayesian model of multivariate normal with  known variance matrix we will find an empirical Bayes confidence interval for the mean vector components which have normal distribution. We will find this empirical Bayes confidence interval as a conditional form on ancillary statistic. In both cases (i.e.  conditional and unconditional empirical Bayes confidence interval), the empiri...

متن کامل

Multivariate Generalized Spatial Signed-Rank Methods

New multivariate generalized signed-rank tests for the one sample location model having favorable efficiency and robustness properties are introduced and studied. Limiting distributions of the tests and related estimates as well as formulae for asymptotic relative efficiencies are found. Relative efficiencies with respect to the classical Hotelling T 2 test (and the mean vector) are evaluated f...

متن کامل

On the Canonical-Based Goodness-of-fit Tests for Multivariate Skew-Normality

It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace tra...

متن کامل

A comparative study on Intolerance of Uncertainty, Emotion Regulation, and Cognitive Avoidance in Patients with Generalized Anxiety Disorder and Healthy People

Introduction: Generalized anxiety disorder is one of the most common anxiety disorders that cognitive and emotional components have an important role in its developing and persistence. So, the aim of this study was to comparing intolerance of uncertainty, emotion regulation (cognitive reappraisal, suppression), and cognitive avoidance in patients with generalized anxiety disorder and healthy in...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Computational Statistics & Data Analysis

دوره 53  شماره 

صفحات  -

تاریخ انتشار 2009