Description Usage Arguments Examples
Get the ordinary least square estimated coefficients on a set of covariates (previously selected by some method
1 | lm.ols.refit(X, Y, intercept, est.betas)
|
X |
covariates (n times p matrix, n: number of entries, p: number of covariates) |
Y |
response (vector with n entries) |
intercept |
TRUE to fit the data with an intercept, FALSE to fit the data without an intercept |
est.betas |
estimated betas from previous fitted result. It can be a vector with p+1 entries (first entry as intercept) or a matrix with p+1 columns. Non-zero coefficient means the corresponding covariate is selected |
1 2 3 4 5 6 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.