All Questions
9 questions
1
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0
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44
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Using multiple individual regressions Y~X_i to find the best two combination of predictors
Problem Statement
Let's say I have multiple solved OLS regressions of the form $Y \sim X_1$, $Y \sim X_2$, ..., $Y \sim X_n$
I want to find which best two combined are the best predictors combined, ...
- 271
1
vote
0
answers
69
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Subtracting predictions from linear regression model & stochastic error [closed]
Understanding that a linear regression model includes stochastic error, can I eliminate error from my model's predictions by subtracting one prediction from the other?
Let's say we have a model of the ...
1
vote
0
answers
563
views
How can I compare the effectiveness of a regression model for different datasets
I have a multiple linear model that works on different datasets. suppose that the first dataset produces y in range of [1,100] and the second one in range of [1, ...
- 213
3
votes
0
answers
914
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Minimize sum of squared errors or its mean
Is there any difference in minimizing the sum of squared errors in a linear regression model learning, compared to minimizing the mean of the sum of squared errors, apart from having easier math when ...
-1
votes
1
answer
34
views
Interpret Model error result.
I have a regression model and used some independent variables to estimate dependent variables.Now I am trying to evaluate the model performance by using percentage bias (p_bias) and Model efficiency (...
- 217
5
votes
2
answers
3k
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Adding Regressors: How Does the Estimated Variance of the Error Terms Change?
Consider the regression model $$Y=X\beta+\epsilon$$ where the error terms in $\epsilon=(\epsilon_1,\ldots,\epsilon_n)^T$ are homoskedastic and where $n$ is the number of observations. Assume that we ...
- 1,109
3
votes
1
answer
531
views
A reasonable multivariate regression error metric
How would you compare error metrics of a multiple output regression? Normalised mean square error for each variable? How about for the overall performance of the model, would you just take the mean ...
- 363
32
votes
1
answer
9k
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How incorrect is a regression model when assumptions are not met?
When fitting a regression model, what happens if the assumptions of the outputs are not met, specifically:
What happens if the residuals are not homoscedastic? If the
residuals show an increasing or ...
- 719
1
vote
1
answer
3k
views
How to Reduce Error Term
My question is "What could you do if you wanted to reduce the error term (e)? I know the error term is basically the distance between the line and the point but I don't know how you would reduce it. ...
- 11