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Results tagged with regression
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user 8101
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
5
votes
2
answers
4k
views
Prediction with GLS
Let's say I build a Generalized Least Squares model. I follow the standard procedure and first estimate a LM model. Then I create an error-response covariance matrix based on the residuals of this mod …
10
votes
2
answers
472
views
Regularization $L_1$ norm and $L_2$ norm empirical study
There are many methods to perform regularization -- $L_0$, $L_1$, and $L_2$ norm based regularization for example. According to Friedman Hastie & Tibsharani, the best regularizer depends on the proble …
- 2,637
2
votes
0
answers
821
views
Are there linear multiple regression methods resilient to missing data?
Are there any multiple linear regression methods or packages that are resilient to occasional missing values? … Although I am not performing a panel regression, my data is arranged as panel data: Date, Identifier for individual in population, Characteristic 1, Characteristic 2 , ... , Objective function value. …
- 35.4k
5
votes
1
answer
1k
views
How to apply Mahalanobis weighted regression in R?
The idea is that in the regression every observation is given a weight as an inverse of the Mahalanobis distance. … However, I do not see a regression technique that allows one to apply this as a robust regression technique. …
- 23k
2
votes
0
answers
441
views
Weighted average semi-parametric regression in R [closed]
An example of such a regression is in the links below.
I see that there is package GAM in R for Generalized Additive Models. … However, it is not clear to me whether this procedure is the same as weighted average semi-parametric regression. …
- 3,091
3
votes
Looking at residuals vs. residual percentages
I would consider normalizing the residual by the Prediction Interval and then proceeding to sort your residuals. A prediction interval is the estimate of an interval in which observations will fall wi …
- 3,091