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: \...
August Edwards's user avatar
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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. ...
Insect_biologist's user avatar
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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 ...
Elizabeth's user avatar
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Box-Cox transformation formula

I am reading some resources about the Box-Cox transformation. Almost all of the websites I found give the formula of the transformation formula as $$y^{(\lambda )} =\begin{cases}\frac{y^\lambda-1}{\...
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Box-Cox data transformation formulas for one and two-way ANOVA [duplicate]

I want to write my own program with box-cox data transformation for ANOVA. I don't understand how to perform a Maximum Likelihood Estimation of λ for my case. I found out how to find optimal λ for ...
trapped_in_a_corner's user avatar
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Can I use different transformations on features to ensure my data follow Gaussian Distribution

Suppose I am doing linear regression on a dataset. My dataset contains columns $f_1, f_2, f_3, f_4, f_5, \text{target}$. Features (independent variables) are the column names starting with "f&...
letdatado's user avatar
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Avoiding negative values in Forecasting

I have questions about the Box-Cox transformation that can be used to maintain positive forecasts (Log-Transform) when $\lambda=0$ \begin{equation} w_t = \begin{cases} \log(y_t) & \...
Rashad Al-Harthy's user avatar
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Should data be centered at $1$ before applying Box-Cox transformation?

Let's suppose that we perform Box-Cox transformation in R for the following data ...
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Total generalized variance for Box-Cox transformed components

I have a couple Gaussian mixture models where each component comes from (component-wise) Box-Cox transformed data. These models do not describe the same data: the individual components are selected ...
ladislaw94's user avatar
1 vote
2 answers
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Heteroscedasticity still present after Box-Cox transformation

I just started to learn regression and I'm trying to fit a linear regression model to some data with one continuous independent variable x1, one categorical variable x2, and the dependent variable y. ...
Vera's user avatar
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The MLE's for $(\beta ,\sigma^2)$ in Box-Cox transformation

Assume that $y=(y_1 ,\ldots ,y_n)$, $y_i >0$. The Box-Cox transformation is $$y(\lambda ) :=\begin{cases}\frac{y^\lambda-1}{\lambda}&\lambda \neq 0\cr \ln y&\lambda =0\end{cases}.$$ In Box-...
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A good reference for power and Box-Cox transformation

I would appreciate if someone could introduce me a good reference for power transformations and Box-Cox transformation. I'm elementary in statistics and I want to learn them properly. Thank you very ...
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Inverting diff() and BoxCox() in R

i'm doing a project with a non-stationary time series. i used BoxCox trasformation and differences to make it stationary ...
Carmine's user avatar
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Comparing means in Box-Cox transformed data

Deeply sorry as this wasn't really covered in my statistics classes. I am current comparing datasets for people divorcing vs. dissolving their marriages. I have two variables, length of marriage, and ...
Sophie's user avatar
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How to apply the Box-Cox transformation to a univariate time series in R?

I have tried to follow the steps indicated on this page and it doesn't work as it doesn't identify the function "recipe" (which I fail to understand anyways...). I am trying to find the best ...
gerardlambert's user avatar
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Need help finding a corresponding distribution

I made a Monte Carlo based hypothesis test, which starts comparing N values in M simulations to a confidence interval, giving me a binary N*M matrix. Then I calculate the percent of values equal to 1 ...
Pedro Caliari's user avatar
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Box-Cox parameter confidence interval clarification

In their original publication, Box and Cox state ...we can obtain an approximate $100(1 - \alpha)$ per cent confidence region [around $\hat{\lambda}$] from $$ L_\text{max} (\hat{\lambda}) - L_\text{...
Anthony's user avatar
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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 <...
Adrian Keister's user avatar
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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 ...
Mew's user avatar
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7 votes
1 answer
2k views

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 ...
Katsu's user avatar
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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 ...
Joey Adams's user avatar
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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 ...
Audison's user avatar
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1 answer
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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 ...
Anthony's user avatar
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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 ...
Bodel's user avatar
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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?
AlejandroDGR's user avatar
1 vote
1 answer
2k views

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 ...
Javier Ventajas Hernández's user avatar
4 votes
1 answer
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 ...
Sujit Desai's user avatar
23 votes
3 answers
3k views

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 ...
Thalassophile's user avatar
4 votes
2 answers
6k views

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 ...
Daniil Yefimov's user avatar
6 votes
3 answers
3k views

Why in Box-Cox method we try to make x and y normally distributed, but that's not an assumption for linear regression?

In Sheather's book, it states that The Box-Cox procedure aims to find a transformation that makes the transformed variable close to normally distributed. To be specific: Also, when x and y are ...
Andre's user avatar
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2 votes
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Normal distribution issues - Log transformations versus distribution fitting

Context: I want to know if the position of the CWD significantly influences Grass Height. I have 2 variables: 1.) a continuous response variable called Grass Height (cm) 2.) a categorical predictor ...
Dominique's user avatar