summary.krls2: Summary function for KRLS2 objects.
In lukesonnet/KRLS: Kernel-based Regularized Least squares
View source: R/summary.krls2.R
Description
Main method for examining results of krls,
much as one would use summary.lm for lm objects. Like its lm analog,
it provides a summary akin to a regression table: average marginal
effects for each input variables, together with standard errors.
Usage
1
summary.krls2(object, probs = c(0.25, 0.5, 0.75), ...)
lukesonnet/KRLS documentation built on May 21, 2019, 8:58 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/summary.krls2.R
Description
Main method for examining results of krls, much as one would use summary.lm for lm objects. Like its lm analog, it provides a summary akin to a regression table: average marginal effects for each input variables, together with standard errors.
Usage
1 | summary.krls2(object, probs = c(0.25, 0.5, 0.75), ...)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.