Linked Questions
10 questions linked to/from Justification for and optimality of $R^2_{adj.}$ as a model selection criterion
14
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4
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When AIC and Adjusted $R^2$ lead to different conclusions
I hope it's okay to ask theoretically driven R questions here.
R has given me the following results from my 'tournament of models'.
All models are entirely distinct except from 3 basic control ...
- 331
14
votes
3
answers
24k
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Which is better: r-squared or adjusted r-squared?
I just started to learn about the following statistical measures, r-squared and adjusted r-squared and was wondering why can't we use adjusted r-squared for every regression model considering the ...
- 153
12
votes
2
answers
3k
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Why information criterion (not adjusted $R^2$) are used to select appropriate lag order in time series model?
In time series models, like ARMA-GARCH, to select appropriate lag or order of the model different information criterion, like AIC, BIC, SIC etc, are used.
My question is very simple, why donot we ...
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2
votes
2
answers
2k
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Adjusted R2 for model with only one independent variable?
Adjusted R2 is said to be more unbiased than ordinary R2 as it takes the number of explanatory variables into account.
Can adjusted R2 be used in a model with only an intercept and one independent ...
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3
votes
1
answer
703
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Where is the divide between information criterion (AIC, BIC, etc...) and cross validation?
I've taken a regression class and am now in a machine learning class. In regression, we talk about model selection using adj-R2 and AIC/BIC. In my machine learning class, we primarily select models ...
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3
votes
1
answer
943
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How to show that a model is not over-fitted?
This might have a very simple answer, but I am doing an analysis of a financial series and have decided to use regression in order to predict a particular revenue given a set of input variables. ...
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1
vote
2
answers
319
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Removing variables from a linear regression improves $R^2_{adj.}$
I am working on a linear regression model.
The complete model with 11 variables in total has a quite low adjusted R-squared ($R^2_{adj.}$) of 0.11.
4 variables have a significant influence on the DV....
- 38
1
vote
0
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354
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How to interpret increase to AIC and adjusted r-squared?
I understand adjusted r-squared and AIC can be used to select an ideal model from a group. Higher AIC is worse but higher ar2 is better.
After adding a categorical variable to an OLS model, my ...
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0
votes
0
answers
215
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Visualize autocorrelation in multiple timeseries one dataset
Background
Performing multiple linear regression analysis on dataset containing 21 time-series of 4 data points. Each data points represents 9 variables.
R² adjusted is not decreasing rapidly after ...
- 31
2
votes
0
answers
87
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When and why should R squared be used instead of adjusted R squared?
The title says it all.
In what situation R squared (non adjusted) is more useful and should be used instead of the adjusted one? Why?
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