10 questions linked to/from Intuition behind Box-Cox transform
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### fractional power transformation [duplicate]

I am making my first thorough exploration of transformations. My primary goal is to improve the normality of the residuals following a mixed effects model fit. For some of my response variables, ...
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### Log or square-root transformation for ARIMA

With the below dataset, I have a series which needs transforming. Easy enough. However, how do you decide which of the SQRT or LOG transformations is better? And how do you draw that conclusion? <...
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### How is the Box-Cox transformation valid?

The Box-Cox transformation transforms our data into a normal distribution. How is that even a proper technique? What if our data didn't come from a normal distribution? How could someone just blindly ...
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### How do I find a variance-stabilizing transformation?

I wonder how to solve this classical problem: Recall that for a binomial proportion $\hat p$ based on a sample of size $n$ we have $$E(\hat p)=p$$ and $$\operatorname{Var}(\hat p) = p(1-p)/n.$$ ...
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### Natural log approximation

I've got an equation that contains $$x^p - 1$$ $x$ is any positive number (such as 2) and $p$ is a small positive number close to 0 (such as 0.001). For some reason (that I may have known in High ...
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### Categorizing river discharge data

I'm struggling with figuring out the best way to break up my river discharge data in a way that I can use it as a factor for further analysis. I'm currently manipulating the data in R but plan to pull ...
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### Simple Problem with Box-Cox Transformation in a Time Series Model

I am running into some problems with data transformations I am doing as part of a time series model I am building. I am doing the following transformations in the following order on my target ...
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### how to select the best non-linear model that represents the data?

I have developed different non-linear models, all of them follow the following formula: y=b0 + b1*(x1)^b2 + b3*(x2)^b4 where y is the dependent variable;x1 and x2 are independent variables;b0, b1, b2, ...