In my research, I aimed to perform a regression model with four predictors and one response variable. When I verified a high collinearity among the predictors, I was instructed to handle this problem using a ridge regression. So, I developed this analysis using R's glmnet package, and I...
I'm interested in the potential effects of water pollution on feather color of a bird. For this, I calculated 4 color variables for each individual (brightness, hue, blue chroma and UV chroma), which are my 4 dependent variables. My independent variables (explanatory) are the...
How can we do weighted ridge regression in R?
In MASS package in R, I can do weighted linear regression by passing a weight parameter to `lm`. It can be seen that the model with weights is different from the one without weights.
# with weights
> model = lm( y ~ X - 1, weights = w)...
I'm currently running a ridge regression in R using the glmnet package, however, I recently ran into a new problem and was hoping for some help in interpreting my results.
My data consists of a 26531x428 observation matrix x and a 26531x1 response vector y. I am attempting to...
I've been trying to run a user-written program to do a ridge and weighted fixed effects panel data regression called xtregfem but I can't get it to work. What I do is:
xtregfem hea gdpln postin labforfem, id(country) it(year)
I have a regression model fit<-lm divorce~unemploy+fem+marriage+birth+military) the data set has 77 observations and 6 variables and interpretted the data.
Now, I need to fit a ridge regression to the data. How do I do that in R?