# Tag Info

### Maximum Likelihood with Categorical Variables - Does this Change Anything?

The algorithm used is exactly the same: although the features are not continuous in your example, the coefficients in a regression model still are. We are optimizing the coefficients in the model, the ...
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### Chi-Square Difference Test for Nested Models with a Continuous Outcome

Chi-square is a distribution, not a test. Chi-square tests are used for things that are chi-square distributed. There are two different things they are used for: The chi-square test of a contingency ...
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### Chi-Square Difference Test for Nested Models with a Continuous Outcome

The term 'chi-squared test' tends to be applied to almost any test that has a test statistic whose distribution under $H_0$ is (at least approximately) distributed as chi-squared. Something similar ...
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### Maximum Likelihood with Categorical Variables - Does this Change Anything?

On the one hand, there are features, which are attributes of your data, stuff that you measure, and on the other hand, there are the parameters to your model. Both can be continuous or discrete. If ...
• 3,138

### Estimating Mixture Models with Maximum Likelihood

While the observed likelihood is a well-defined function $$L(\theta|\mathbf x)=\prod_{i=1}^n \{\pi_1\varphi(x_i;\mu_1,\sigma_1)+ (1-\pi_1)\varphi(x_i;\mu_2,\sigma_2)\}$$ it does not offer enough ...
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Accepted

• 94.7k
1 vote
Accepted

### How to get most likely value with confidence interval or expected value from a set of observations

A key comment above is @Bernhard's statement that you may need to make additional assumptions for a good answer. One reasonable assumption is that the data are normal. Descriptive statistics (fron R) ...
• 50k
1 vote

### Statistical comparison of (covariance) matrices

My favorite tool for comparing covariances comes from Förstner W., Moonen B. A Metric for Covariance Matrices. In: Grafarend E.W., Krumm F.W., Schwarze V.S. (eds) Geodesy-The Challenge of the 3rd ...
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