Hi,

I tried to install Deducer on an Gentoo Linux AMD64 and received the
following error messages:

install.packages("Deducer",,"http://cran.r-project.org")
trying URL 'http://cran.r-project.org/src/contrib/Deducer_0.1-0.tar.gz'
Content type 'application/x-gzip' length 2123646 bytes (2.0 Mb)
opened URL
==================================================
downloaded 2.0 Mb

* Installing *source* package 'Deducer' ...
** R
** inst
** preparing package for lazy loading
Loading required package: proto
Loading required package: grid
Loading required package: reshape
Loading required package: plyr

Attaching package: 'ggplot2'


        The following object(s) are masked from package:grid :

         nullGrob

Error : package 'JGR' 1.7-0 was found, but < 1.7 is required by 'Deducer'
ERROR: lazy loading failed for package 'Deducer'
* Removing '/usr/lib64/R/library/Deducer'

The downloaded packages are in
        '/tmp/RtmpWnRZ0y/downloaded_packages'
Updating HTML index of packages in '.Library'
Warning message:
In install.packages("Deducer", , "http://cran.r-project.org") :
  installation of package 'Deducer' had non-zero exit status

Jan Vandermeer


On Mon, Aug 3, 2009 at 2:21 PM, Ian Fellows <ifellows@ucsd.edu> wrote:

> Hi All,
>
>   I am seeking comments, suggestions, bugs, and users for a data analysis
> GUI that has just been released to CRAN. One of the first areas that I
> think
> that this GUI could be of use is in the classroom, so your comments would
> be
> very valuable to me. An online manual is available (though under
> construction) here:
>
> http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual
>
>   I'd appreciate any feedback or bugs. I'm particularly interested in
> experiences using it from within non-JGR GUI's, and under Linux. If any of
> you teach introductory/intermediate statistics, I'd like to know how you
> would feel about using it in the classroom.
>
> TIA,
> Ian
>
>
> p.s. Installation instructions:
> install.packages("Deducer",,"http://cran.r-project.org")
>
>
>
>
> ---------------------------------------------------------------------------
>
>
> 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
>
> _______________________________________________
> R-sig-teaching@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
>

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