The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Input datasets are available in Cornerstone and you can select variables in this dataset for each analysis, e.g., the R interface. R functions can be defined with more than one input dataset. This function redirects a Cornerstone dataset into an R object which can be used as an 'Input R Object' in the R interface as shown in the following screenshot.
As in the screenshot above, we will use the sample dataset 'gas90' for this explanation.
To achieve the result in 'Cornerstone' open a dataset and choose menu 'Analysis' -> 'CornerstoneR' -> 'Redirect Dataset to R Object' as shown in the following screenshot.
In the appearing dialog select variable all interesting variables to predictors. It is possible to assign variables to responses, group, and auxiliaries. This information is piped to the redirected dataset and can be used in other functions.
'OK' confirms your selection and the following window appears.
Now, click the execute button (green arrow) or choose the menu 'R Script' -> 'Execute' and all calculations are done via 'R'. Calculations are done if the text at the lower left status bar contains 'Last execute error state: OK'. Our result is available via the menu 'Summaries' -> 'Redirected Dataset' as shown in the following screenshot.
After clicking this menu a 'Cornerstone' object with the redirected data opens.
After you create another analysis (in this example we use 'matchNearestNeighbor' from the dataset 'gas91') we can chose the redirected dataset in the 'R' object via 'R Script' -> 'Input R Objects'.
In the appearing dialog select the corresponding object.
'OK' confirms your selection and you get back to the 'R Script' window.
Now, click the execute button (green arrow) or choose the menu 'R Script' -> 'Execute' and all calculations are done via 'R' within 'matchNearestNeighbor'. If you selected the same variables as predictors as in the redirected dataset, can get the results from this calculation via 'Summaries' -> 'Nearest Neighbors'. This dataset shows for each row in 'gas91' the corresponding row from 'gas90' with the lowest Euclidean distance. You find a detailed explanation in the corresponding vignette.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.