I would like to perform a chi^2 goodness of fit test in Matlab and have found the function h = chi2gof(x) to do almost what I want. The only issue is that I want to perform the fit about a proposed mean and not the mean that chi2gof automatically estimates from the data.
Matlab Chi^2 Goodness of fit test for specified mean
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I am going to answer starting with the point that seems to generate confusion:
The only issue is that I want to perform the fit about a proposed mean and not the mean that chi2gof automatically estimates from the data.
1.-
chi2gofdoes not estimate a mean from datachi2gofestimates how likely is the supplied data to be the pdf that you tellchi2gofit may be.You supply the likely pdf therefore you supply the mean and other statistical moments that the data may or may not show.
2.- By default normal aka Gaussian
If you input just
xthe datachi2gofassumes it's a normal distribution with significance levelp = 0.05If the data is generated as normal with
mean=100andsigma=1thenchi2gofsolvesis
xnormal with significance level aka p=0.05 ?To change the significance level
The default significance level by default is 0.05 .
There has been some initiative to change such 0.05 default value down to 0.005 but it backfired, the experts casting further doubt on being able at all to pontificate around a bare threshold, details in article Moving to a world beyond p<0.05, authors: R.L.Wasserstein,A.L.Schirm, N.A.Lazar Mar20th 2019 American Statistician .
3.-
AlphaIS NOT mean(x)Alphais a threshold for significance levelp.Alpha=0.01means the probability of errors or false positives being 1 in 100 samples, on average.4.- To change the reference distribution in chi2gof use field CDF
First define the specific distribution with the particular mean you are aiming at, for instance
and then use pd in
chi2gofThe complete
chi2gofhelp file is available online herehttps://www.mathworks.com/help/stats/chi2gof.html