Showing content from http://cran.rstudio.com/web/packages/rJava/../CirceR/../rmarkdown/../ECTSVR/vignettes/ECTSVR.Rmd below:
--- title: "ECTSVR" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{ECTSVR} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` ## Introduction \*\*\*\*
*The cointegration based support vector regression model is a combination of error correction model and support vector regression ( ). This hybrid model allows the researcher to make use of the information extracted by the cointegrating vector as an input in the support vector regression model.* \*\*\*\*
```{r setup} # Examples: How The cointegration based support vector regression model can be applied library(ECTSVR) #taking data finland from the r library data(finland) #takaing the two cointegrated variables (4th and 3rd) from the data set data_example <- finland[,4:3] #application of ECTSVR model with radial basis kernel function of Epsilon support vector regression model ECTSVR(data_example,"trace",0.8,2, "radial","eps-regression",verbose = FALSE) ```
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