Stochastic Processes
Variance stabilization refers to the process of transforming random variables so that their variance becomes constant across different levels of the variable. This is particularly important in statistical modeling and analysis, as it allows for more reliable estimates and predictions by addressing issues of heteroscedasticity, where variability changes with the level of the variable. Techniques used for variance stabilization often include logarithmic transformations, square root transformations, and other methods designed to normalize the variance.
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