Visualizing hypothesis tests in multivariate linear models: theheplotspackage for R
โ Scribed by John Fox; Michael Friendly; Georges Monette
- Book ID
- 105855279
- Publisher
- Springer
- Year
- 2008
- Tongue
- English
- Weight
- 495 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0943-4062
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
An approximate degrees of freedom test is suggested for hypotheses of the kind H 0 : C$8 1 M=C$8 2 M in two independent multivariate linear models: Y i =X i 8 i += i , i=1, 2, under the assumption of error matrix variate normality and heteroscedasticity. It is shown for specific vector choices of th
The null hypothesis that the error vectors in a multivariate linear model are independent is tested against the alternative hypothesis that they are dependent in some specified manner. This dependence is assumed to be due to common random components or autocorrelation over time. The testing problem
This paper is concerned with the null distribution of test statistic T for testing a linear hypothesis in a linear model without assuming normal errors. The test statistic includes typical ANOVA test statistics. It is known that the null distribution of T converges to w 2 when the sample size n is l