CRAN
KSPM 0.1.2
Kernel Semi-Parametric Models
Released Apr 7, 2019 by Catherine Schramm
Dependencies
DEoptim 2.2-4 CompQuadForm 1.4.3 expm 0.999-4
To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables.
Installation
Maven
This package can be included as a dependency from a Java or Scala project by including
the following your project's pom.xml
file.
Read more
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>KSPM</artifactId> <version>0.1.2-b1</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:KSPM')
Test Results
This package was last tested against Renjin 0.9.2725 on May 4, 2019.
- coef.kspm-examples
- confint.kspm-examples
- deviance.kspm-examples
- extractAIC.kspm-examples
- fitted.kspm-examples
- kspm-examples
- logLik.kspm-examples
- nobs.kspm-examples
- plot.derivatives-examples
- plot.kspm-examples
- predict.kspm-examples
- residuals.kspm-examples
- stepKSPM-examples
- summary.kspm-examples
- test-kernelfunction.kernel_gaussian_works_E1
- test-kernelfunction.kernel_gaussian_works_E2
- test-kernelfunction.multiplication_works
- test-testfile.multiplication_works
- testthat