According to Wludyka and Nelson (1997), the Analysis of Means (ANOM), which is a test of location, can be converted into a test of scale and used to test the homogeneity of variances test, when the normality assumption is reasonable.
The analysis of means for variances (ANOMV) is used for testing the k-sample homogeneity of variantes hypothesis for independent samples of size n from normal populations. The test can be done in a graphical form and has been shown to have power comparable to the best competing tests. For details and examples see Wludyka and Nelson (1997).
This m-file considers that all the factor levels have equal sample size (balanced), and with the known assumption that the errors e_ij are approximately normally distributed.
Here, we use the statistical fundamentals and procedure given by Wludyka and Nelson (1997). You can find charts with the variances. Instead, here we use the standard deviations for it linear behavior.
Inputs:
X - data matrix (Size of matrix must be n-by-2; data=column 1, sample=column 2).
a - significance level (default = 0.05).
Outputs:
- Complete Balanced Analysis of Means for Variances
- ANOMVARBAL chart
引用格式
Antonio Trujillo-Ortiz (2024). anomvarbal (https://www.mathworks.com/matlabcentral/fileexchange/23855-anomvarbal), MATLAB Central File Exchange. 检索时间: .
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