# Questions tagged [boxcox-transformation]

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### Optimization of relative error vs optimization on log scale

I am currently training a model to predict house sales prices, $P$, as a function of a set of characteristics $\textbf{x}$. The model I have chosen is a log-specified regression model of the form: \...
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### Is there a way to calculate lambda for a Box-Cox transformation when there are two categorical independent variables in R?

I have the following model where X is the duration of a particular event, A is a factor with five levels and B is a factor with two levels. I want to run a type III ANOVA analysis. ...
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### Is there a by-group interaction issue after the Box-Cox transformation?

I've come across a question that has me a bit stumped and hope to seek your valuable insights. Specifically, I've been working with the Box-Cox Transformation to normalize dependent variables within ...
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### Which transformation in a linear regression should I use when variance is larger on the small end?

Note: this is part of Exercise 5.6 in Design and Analysis of Experiments, 2nd Ed., by Dean, Voss, and Draguljic. If you go here and download the bicycle.txt dataset, then run some R commands such as <...
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### Optimising Box-Cox lambda analytically

I'm taking a university course in statistics where the Box-Cox transform is being discussed. As I understand it, we assume that there is some $\lambda$ that makes the sample normally distributed after ...
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### Interpreting the Lambdas of Yeo Johnson Transformation?

The following is the table of Lambda values that describe what the resulting dataset would look like after a Box Cox transformation: What is the equivalent table for Yeo Johnson's lambda values? Cant ...
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### How to find the transformed density and log likelihood for this family of distributions?

Let's consider the family of transformations given by $$g_a(Y)=\begin{cases} \frac{e^{aY}-1}{a} & \text{ for } a\neq 0 \\ Y & \text{ for } a=0 \end{cases}$$ for $Y\in\mathbb{R}$. Analogous to ...
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### Optimization of Box-Cox and Yeo-Johnson Log-Likelihood function

This question is a continuation of this question: Derivation of Box-Cox and Yeo-Johnson Log-Likelihood Functions. In order to derive the maximum lambda value in log-likelihood objective function for ...
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### Derivation of Box-Cox and Yeo-Johnson Log-Likelihood Functions

The scipy documention lists expressions for the Log-likelihood functions for the Box-Cox and Yeo-Johnson transformations here and here. I'm looking for a source ...
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### Multiple comparisons of Box-Cox transformed data

I'm working on a dataset of highly-skewed data that I have transformed using Box-Cox. I have 2 groups (healthy controls and diseased participants) and I need to perform multiple comparisons (to ...
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### What can OLS with a Box-Cox transformed dependent variable tell me?

Just to ellaborate: I’m doing an OLS-test to determine the following things: Do my independent variables have a significant effect on the dependent variable? What’s the direction of the effect of my ...
364 views

### Is there any alternative way to Box-Cox transformations to stabilize the variance of a time series?

My question is straightforward: Is there any alternative way to Box-Cox transformations to stabilize the variance of a time series?
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### Box-Cox transform doesn't make data normal

I'm working with the famous diamonds dataset and the target value is non-normal: After applying the Box-Cox transform, the shape of the histogram is closer to a normal distribution but the quantile ...
534 views

### Using Box-Cox transformed features as input decreased the $R^2$ score of a regression model

I am working on building a regression model to predict housing sales price using house features (Ames housing dataset). And I prepared feature set in two ways: Case 1. I performed Box-Cox ...
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### Intuition behind Box-Cox transform

For features that are heavily skewed, the Transformation technique is useful to stabilize variance, make the data more normal distribution-like, improve the validity of measures of association. I am ...
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### Parameter $\lambda$ of Box-Cox transformation and likelihood

In the Box-Cox transformation parameter $\lambda$ is defined by likelihood function. But I cannot understand what exactly is maximized in this case? What is the purpose of maximum-likelihood in this ...
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