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### Back transformation of an MLR model [duplicate]

I've obtained a multiple linear regression model in the form  \mathrm{log}(Y) = \beta_0 + \beta_1x_1 + \dots + \beta_4x_4 + \beta_5x_1x_2 + \dots + \beta_{10}x_3x_4 + \beta_{11}x_1^2 + \dots + \...
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### Linear regression with log transformed data - large error [duplicate]

I have a set of data which is has a very large positive skew, and has been transformed using a logarithm. I wish to predict one variable from another using the lm ...
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### Training the learning model on the log transformed data? [duplicate]

So I've gone through this CV post, and in my primitive understanding I assume we do log transformation when we 'care' about relative changes and also to even out the positive skweness from our data. ...
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### Prediction interval for log transformed variable in Stata [duplicate]

I want to predict $y$ with $x_1$ and $x_2$, including an out of sample prediction interval. However, $y$ has large outliers, so I log transform $y$ and estimate $\log(y) = a + b_1 x_1 + b_2 x_2 + e$, ...
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### Back-transformed confidence intervals

Having come across this discussion I'm raising the question on the back-transformed confidence intervals conventions. According to this article the nominal coverage back-transformed CI for the mean ...
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### Back Transformation

If I had a response variable that was square-root transformed, and an explanatory variable that is log transformed, and I wished to back transform the model using the summary statistics below, such ...
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### Evaluation of log Vs. non log models

There are several posts on here about this question. The gist of them, as far as I understand, is that you cannot compare RMSE or MAE of two models where one is log transformed on the dependent ...
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### How to deal with predictions if taking log of dependent variable

I have a very basic question about linear regression. I have a dataset where the response variable is largely skewed to the right -- if I take a log of it, the distribution becomes a lot closer to ...
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### Why Does a Monotonic Transformation Of Dependent Variable Change Variance Explained In Random Forest

I am working with the Boston data set in R. I have read that random forest should be able to deal with untransformed data. In my example I do a log transformation of the dependent variable. My ...