[RsR] Rcmd and robust tools
Eva Cantoni
Ev@@C@nton| @end|ng |rom un|ge@ch
Wed Aug 12 10:10:02 CEST 2009
Thank you to all of you for your suggestions. We will evaluate the
options in light of our needs and decide what to do.
Best regards,
Eva Cantoni
Rudi Dutter wrote:
> Hi Eva,
>
> Thanks to Valentin for the nice remarks.
>
> In our group we are developing a package called DAS+R on the basis of
> the Rcommander. A very preliminary version is available from
> http://www.statistik.tuwien.ac.at/StatDA/DASplusR/
> It particularly considers spatial data and only has small attempts to
> use robust methods at the moment (e.g. in generating a well scaled
> background map).
>
> We do not have much experience in using the system in teaching,
> nevertheless we observed that students accept and enjoy very much the
> possibility of clicking instead of learning commands by hard. So I would
> be very much interested in a cooperation and exchange of ideas.
>
> Best regards,
> Rudi
>
> Valentin Todorov wrote:
>
>> Dear Eva,
>>
>> The recent book:
>>
>> Statistical Data Analysis Explained: Applied Environmental Statistics with R
>> by C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter; Wiley,
>> Chichester, 2008.
>>
>> uses both (a modified) R Commander and robust methods, but I hope
>> Peter Filzmoser and Rudi Dutter read also this list and can tell more.
>>
>>
>> Best regards,
>> Valentin
>>
>>
>>
>>
>>
>> On Tue, Aug 4, 2009 at 5:26 PM, Ian Fellows<ifellows using ucsd.edu> wrote:
>>
>>
>>> Hi Eva,
>>>
>>> I'm not sure about Rcmdr, but I just released the Deducer package to CRAN
>>> which uses HCCM by default with linear models. The online manual gives some
>>> screenshots, but I have yet to write the regression page.
>>>
>>> Manual:
>>> http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual
>>>
>>> Cheers,
>>> Ian Fellows
>>>
>>> Announcement:
>>> ---------------------------------------------------------------------------
>>>
>>>
>>> Deducer 0.1 has been released to CRAN
>>>
>>> Deducer is designed to be a free, easy to use, alternative to proprietary
>>> software such as SPSS, JMP, and Minitab. It has a menu system to do common
>>> data manipulation and data analysis tasks, and an excel-like spreadsheet in
>>> which to view and edit data frames. The goal of the project is to two fold.
>>>
>>> 1. Provide an intuitive interface so that non-technical users
>>> can learn and perform analyses without programming getting
>>> in their way.
>>> 2. Increase the efficiency of expert R users when performing
>>> common tasks by replacing hundreds of keystrokes with a few
>>> mouse clicks. Also, as much as possible the GUI should not
>>> get in their way if they just want to do some programming.
>>>
>>> Deducer is integrated into the Windows RGui, and the cross-platform Java
>>> console JGR, and is also usable and accessible from the command line.
>>> Screen shots and examples can be viewed in the online wiki manual:
>>>
>>> http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual
>>>
>>> Comments and questions are more than welcome. A discussion group has been
>>> created for any questions or recommendations.
>>>
>>> http://groups.google.com/group/deducer
>>>
>>> Deducer Features:
>>>
>>> Data manipulation:
>>> 1. Factor editor
>>> 2. Variable recoding
>>> 3. data sorting
>>> 4. data frame merging
>>> 5. transposing a data frame
>>> 6. subseting
>>>
>>> Analysis:
>>> 1. Frequencies
>>> 2. Descriptives
>>> 3. Contingency tables
>>> a. Nicely formatted tables with optional
>>> i. Percentages
>>> ii. Expected counts
>>> iii. Residuals
>>> b. Statistical tests
>>> i. chi-squared
>>> ii. likelihood ratio
>>> iii. fisher's exact
>>> iv. mantel haenszel
>>> v. kendall's tau
>>> vi. spearman's rho
>>> vii. kruskal-wallis
>>> viii. mid-p values for all exact/monte carlo tests
>>> 4. One sample tests
>>> a. T-test
>>> b. Shapiro-wilk
>>> c. Histogram/box-plot summaries
>>> 5. Two sample tests
>>> a. T-test (student and welch)
>>> b. Permutation test
>>> c. Wilcoxon
>>> d. Brunner-munzel
>>> e. Kolmogorov-smirnov
>>> f. Jitter/box-plot group comparison
>>> 6. K-sample tests
>>> a. Anova (usual and welch)
>>> b. Kruskal-wallis
>>> c. Jitter/boxplot comparison
>>> 7. Correlation
>>> a. Nicely formatted correlation matrices
>>> b. Pearson's
>>> c. Kendall's
>>> d. Spearman's
>>> e. Scatterplot paneled array
>>> f. Circle plot
>>> g. Full correlation matrix plot
>>> 8.Generalized Linear Models
>>> a. Model preview
>>> b. Intuitive model builder
>>> c. diagnostic plots
>>> d. Component residual and added variable plots
>>> e. Anova (type II and III implementing LR, Wald and F tests)
>>> f. Parameter summary tables and parameter correlations
>>> g. Influence and colinearity diagnostics
>>> h. Post-hoc tests and confidence intervals
>>> with (or without) adjustments for multiple testing.
>>> i. Custom linear hypothesis tests
>>> j. Effect mean summaries (with confidence intervals), and
>>> plots
>>> k. Exports: Residuals, Standardized residuals, Studentized
>>> residuals, Predicted Values (linear and link), Cooks
>>> distance, DFBETA, DFFITS, hat values, and Cov Ratio
>>> l. Observation weights and subseting
>>> 9. Logistic Regression
>>> a. All GLM features
>>> b. ROC Plot
>>> 10. Linear Model
>>> a. All GLM features
>>> b. Heteroskedastic robust tests
>>>
>>> -----Original Message-----
>>> From: r-sig-robust-bounces using r-project.org
>>> [mailto:r-sig-robust-bounces using r-project.org] On Behalf Of Eva Cantoni
>>> Sent: Tuesday, August 04, 2009 6:51 AM
>>> To: r-sig-robust
>>> Subject: [RsR] Rcmd and robust tools
>>>
>>> Hi everybody:
>>>
>>> within our applied undergraduate courses, we would like to teach some
>>> robust approaches (essentially multiple regression and covariance matrix
>>> estimation) using R and the R commander Graphical User Interface (Rcmd).
>>> Did anybody in this list already extend the R commander to include
>>> robust methods (either from the robust or robustbase package), or is
>>> anybody interested in collaborating to add this facility to Rcmd ?
>>>
>>> Best regards,
>>> Eva
>>>
>>> --
>>>
>>> Dr Eva Cantoni phone : (+41) 22 379 8240
>>> Econométrie - Univ. Genève fax : (+41) 22 379 8299
>>> 40, Bd du Pont d'Arve e-mail : Eva.Cantoni using unige.ch
>>> CH-1211 Genève 4 http://www.unige.ch/ses/metri/cantoni
>>>
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>
>
--
Dr Eva Cantoni phone : (+41) 22 379 8240
Econométrie - Univ. Genève fax : (+41) 22 379 8299
40, Bd du Pont d'Arve e-mail : Eva.Cantoni using unige.ch
CH-1211 Genève 4 http://www.unige.ch/ses/metri/cantoni
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