The R Project SVN – R – Diff – /branches/R-exp-API/FAQ

 R FAQ
 Frequently Asked Questions on R
-Version 0.90-4, 1999/11/13
+Version 0.90-5, 1999/12/22
 Kurt Hornik
 Table of Contents
 *****************
    The current stable Unix/Windows version is 0.90.1, the unstable one is
 .99.0.  Typically, new features are introduced in the development
 versions; updates of stable versions are for bug fixes mostly.  The version
 for the Mac is pre-alpha.
+   The release of version 1.0 is scheduled for February 29, 2000.
 .4 How can R be obtained?
 ==========================
    Sources, binaries and documentation for R can be obtained via CRAN, the
 "Comprehensive R Archive Network" (see *Note What is CRAN?::).
 font-end called `R' are created and copied to the `bin' directory.  You can
 copy the script to a place where users can invoke it, for example to
 `/usr/local/bin'.  In addition, plain text help pages as well as HTML and
 LaTeX versions of the documentation are built.
-   Use `make dvi' to obtain a dvi version of the R manual.  This creates
+   Use `make dvi' to create dvi versions of the R manuals, such as
-the files `Manual.dvi' (a start of a manual) and `Reference.dvi' (an R
+`refman.dvi' (an R object reference index) and `R-exts.dvi', the "R
-object reference index) in the `doc/manual' subdirectory.  These files can
+Extension Writers Guide", in the `doc/manual' subdirectory.  These files
-be previewed and printed using standard programs such as `xdvi' and `dvips'.
+can be previewed and printed using standard programs such as `xdvi' and
+`dvips'.  You can also use `make pdf' to build PDF (Portable Document
+Format) version of the manuals, and view these using Acrobat.  Manuals
-(Note that they have to be built in the source tree.)
+written in the GNU Texinfo system can also be converted to info files
+suitable for reading online with Emacs or standalone GNU Info; use `make
+info' to create these versions.
    Finally, use `make check' to find out whether your R system works
 correctly.
    You can also perform a "system-wide" installation using `make install'.
      $ ./configure --prefix=/where/you/want/R/to/go
 (E.g., the R executable will then be installed into
 `/where/you/want/R/to/go/bin'.)
+   To install dvi, info and PDF versions of the manuals, use `make
+install-dvi', `make install-info' and `make install-pdf', respectively.
 .5.2 How can R be installed (Windows)
 --------------------------------------
    The `bin/windows/windows-NT' directory of a CRAN site contains the
 latest binary distributions of R for 32 bit versions of MS Windows (i.e.,
 exists, and can be printed on-screen by typing `help(NAME)' (or `?NAME') at
 the R prompt, where NAME is the name of the topic help is sought for.  (In
 the case of unary and binary operators and control-flow special forms, the
 name may need to be be quoted.)
-   This documentation can also be made available as HTML, and as hardcopy
+   This documentation can also be made available as one reference manual
+for on-line reading in HTML and PDF formats, and as hardcopy via LaTeX, see
-via LaTeX, see *Note How can R be installed?::.  An up-to-date HTML version
+*Note How can R be installed?::.  An up-to-date HTML version is always
-is always available for web browsing at `http://stat.ethz.ch/R/manual/'.
+available for web browsing at `http://stat.ethz.ch/R/manual/'.
-   An earlier attempt at an R manual ("Notes on R:  A Programming
+   Currently, three further R manuals are being written:
+   * "An Introduction to R" (`R-intro') includes information on data types,
+     programming elements, statistical modelling and graphics.  This
-Environment for Data Analysis and Graphics"), based on the "Notes on
+     document is based on the "Notes on S-PLUS" by Bill Venables
-S-PLUS" by Bill Venables <venables@stats.adelaide.edu.au> and David Smith
+     <venables@stats.adelaide.edu.au> and David Smith
+     <D.M.Smith@lancaster.ac.uk>.
+   * "R Language Definition" (`R-lang') is the "Kernighan & Ritchie of R",
-<D.M.Smith@lancaster.ac.uk>, can be obtained as `Rnotes.tgz' (LaTeX source)
+     explaining evaluation, parsing, object oriented programming, computing
+     on the language, and so forth.
+   * "Writing R Extensions" (`R-exts') currently desribes the process of
-in a CRAN `doc' directory.  Further documentation on R and the R API are
+     creating R add-on packages, writing R documentation, and R's system
+     and foreign language interfaces, and will soon also contain
-currently being written.
+     information on R's APIs.
+The "R Extension Writers Guide" already comes with R, the other two will be
+available for the 1.0 release.
-   In the absence of an R manual, documentation for S/S-PLUS (see *Note R
+   In addition to material written specifically for R, documentation for
-and S::) can be used in combination with this FAQ (*note What are the
+S/S-PLUS (see *Note R and S::) can be used in combination with this FAQ
-differences between R and S?::).  We recommend
+(*note What are the differences between R and S?::).  We recommend
      W. N. Venables and B. D. Ripley (1999), "Modern Applied Statistics with
      S-PLUS.  Third Edition".  Springer, ISBN 0-387-98825-4.
 which has a home page at `http://www.stats.ox.ac.uk/pub/MASS3/' providing
 Note that the r-announce list is gatewayed into r-help, so you don't need
 to subscribe to both of them.
    Send email to <r-help@lists.r-project.org> to reach everyone on the
 r-help mailing list.  To subscribe (or unsubscribe) to this list send
-`subscribe' (or `unsubscribe') in the BODY of the message (not in the
+`subscribe' (or `unsubscribe') in the _body_ of the message (not in the
-subject!)  to <r-help-request@lists.r-project.org>.  Information about the
+subject!) to <r-help-request@lists.r-project.org>.  Information about the
 list can be obtained by sending an email with `info' as its contents to
 <r-help-request@lists.r-project.org>.
    Subscription and posting to the other lists is done analogously, with
 `r-help' replaced by `r-announce' and `r-devel', respectively.
 which carry identical material, consisting of the R distribution(s), the
 contributed extensions, documentation for R, and binaries.
    The CRAN master site can be found at the URL
-     `http://cran.r-project.org/'                (Austria)
+     `http://cran.r-project.org/'     (Austria)
 (which is the same as `http://cran.at.r-project.org/') and is currently
 being mirrored daily at
-     `http://cran.dk.r-project.org/'             (Denmark)
+     `http://cran.dk.r-project.org/'  (Denmark)
-     `http://cran.it.r-project.org/'             (Italy)
+     `http://cran.it.r-project.org/'  (Italy)
-     `http://cran.ch.r-project.org/'             (Switzerland)
+     `http://cran.ch.r-project.org/'  (Switzerland)
-     `http://cran.uk.r-project.org/'             (United Kingdom)
+     `http://cran.uk.r-project.org/'  (United Kingdom)
-     `http://cran.us.r-project.org/'             (USA/Wisconsin)
+     `http://cran.us.r-project.org/'  (USA/Wisconsin)
 Please use the CRAN site closest to you to reduce network load.
    From CRAN, you can obtain the latest official release of R, daily
 snapshots of R (copies of the current CVS trees), as gzipped and bzipped
 tar files or as two gzipped tar files (ready for 1.4M floppies), a wealth
 of additional contributed code, as well as prebuilt binaries for various
-operating systems (Linux, Nextstep, MacOS, MSWin) and pre-formatted help
+operating systems (Linux, Digital Unix, and MS Windows) and pre-formatted
-pages.  CRAN also provides access to documentation on R, existing mailing
+help pages.  CRAN also provides access to documentation on R, existing
-lists and the R Bug Tracking system.
+mailing lists and the R Bug Tracking system.
    To "submit" to CRAN, simply upload to
 `ftp://cran.r-project.org/incoming' and send an email to
 <wwwadmin@cran.r-project.org>.
 All of the Rweb versions can analyze Web accessible datasets if a URL is
 provided.
    A paper on Rweb, providing a detailed explanation of the different
 versions of Rweb and an overview of how Rweb works, was published in the
+Journal of Statistical Software
-Journal of Statistical Software (`http://www.stat.ucla.edu/journals/jss/').
+(`http://www.stat.ucla.edu/journals/jss/v04/i01').
 R Add-On Packages
 *******************
 .1 Which add-on packages exist for R?
      Functions for kernel smoothing (and density estimation) corresponding
      to the book "Kernel Smoothing" by M. P. Wand and M. C. Jones, 1995.
 *MASS*
      Functions and datasets from the main library of Venables and Ripley,
-     "Modern Applied Statistics with S-PLUS".  Contained in `VR'.
+     "Modern Applied Statistics with S-PLUS".  Contained in the `VR' bundle.
 *NISTnls*
      A set of test nonlinear least squares examples from NIST, the U.S.
      National Institute for Standards and Technology.
 *chron*
      A package for working with chronological objects (times and dates).
 *class*
      Functions for classification (k-nearest neighbor and LVQ).  Contained
-     in `VR'.
+     in the `VR' bundle.
 *cluster*
      Functions for cluster analysis.
 *coda*
      vector of input dates in any of the forms `8/30/53', `30Aug53', `30
      August 1953', ..., `August 30 53', or any mixture of these.
 *e1071*
      Miscellaneous functions used at the Department of Statistics at TU Wien
-     (E1071).
+     (E1071), including moments, short-time Fourier transforms, Independent
+     Component Analysis, and simulation of a Wiener process.
 *fracdiff*
      Maximum likelihood estimation of the parameters of a fractionally
      differenced ARIMA(p,d,q) model (Haslett and Raftery, Applied
      Statistics, 1989).
 *nlme*
      Fit and compare Gaussian linear and nonlinear mixed-effects models.
 *nnet*
      Software for single hidden layer perceptrons ("feed-forward neural
-     networks"), and for multinomial log-linear models.  Contained in `VR'.
+     networks"), and for multinomial log-linear models.  Contained in the
+     `VR' bundle.
 *norm*
      Analysis of multivariate normal datasets with missing values.
 *oz*
      Bowman and A. Azzalini (1997), Oxford University Press.
 *spatial*
      Functions for kriging and point pattern analysis from "Modern Applied
      Statistics with S-PLUS" by W. Venables and B. Ripley.  Contained in
-     `VR'.
+     the `VR' bundle.
 *stable*
      Density, distribution, quantile and hazard functions of a stable
      variate; generalized linear models for the parameters of a stable
      distribution.
 *stataread*
      Read and write Stata v6 `.dta' files.
 *survival5*
-     Functions for survival analysis, version 5 (requires *splines* and
+     Functions for survival analysis, version 5 (suggests *date*), the main
-     suggests *date*), the main new feature being penalised (partial)
+     new feature being penalised (partial) likelihood.
-     likelihood.
 *tree*
      Classification and regression trees.
 *tripack*
    There is also a CRAN `src/contrib/Devel' directory which contains
 packages still "under development" or depending on features only present in
 the current development versions of R.  Volunteers are invited to give
 these a try, of course.  This area of CRAN currently contains
-*bats*
-     Basic time series modelling functions.
 *dopt*
      Finding D-optimal experimental designs.
+*foreign*
+     Functions for reading data stored by statistical software like Minitab,
+     SAS, SPSS, etc.
 *tcltk*
      Basic interface with Tcl/Tk.
 *timeslab*
      Time series routines.
 .2 How can add-on packages be installed?
 =========================================
    (Unix only.)  The add-on packages on CRAN come as gzipped tar files
-(which may contain more than one package).  First "unpack" the files of
+named `PKG_VERSION.tar.gz', which may in fact be "bundles" containing more
-interest.  If you have GNU tar, you can use `tar zxf NAME', otherwise you
+than one package.  Provided that `tar' and `gzip' are available on your
-can use `gunzip -c NAME | tar xf -'.
+system, type
-   Let PKGDIR_1, ..., PKGDIR_N be the (relative or absolute) path names of
-the packages to be installed.  (In the simplest case, the unpacking creates
-a single package directory, and its name is used.)  To install to the
-default R directory tree (the `library' subdirectory of `R_HOME'), type
-     $ R INSTALL PKGDIR_1 ... PKGDIR_N
+     $ R INSTALL /path/to/PKG_VERSION.tar.gz
-at the shell prompt.  To install to another tree (e.g., your private one),
+at the shell prompt to install to the default R directory tree (the
+`library' subdirectory of `R_HOME').  To install to another tree (e.g.,
-use
+your private one), use
-     $ R INSTALL -l LIB PKGDIR_1 ... PKGDIR_N
+     $ R INSTALL -l LIB /path/to/PKG_VERSION.tar.gz
 where LIB gives the path to the library tree to install to.
-   As of R version 0.65.1, you no longer need to explicitly unpack for
+   Even more conveniently, you can install and automatically update
-installing; i.e., you can do `R INSTALL /path/to/pkg_ver.tar.gz'.
+packages from within R if you have access to CRAN.  See the documentation
+for `CRAN.packages()' for more information.
    You can use several library trees of add-on packages.  The easiest way
 to tell R to use these is via the environment variable `R_LIBS' which
 should be a colon-separated list of directories at which R library trees
 are rooted.  You do not have to specify the default tree in `R_LIBS'.
      cluster      Functions for clustering
      ctest        Classical tests
      date         Functions for handling dates
      eda          Exploratory Data Analysis
      gee          Generalized Estimating Equation models
-     lme          Linear mixed effects library
      locfit       Local regression, likelihood and density estimation
      lqs          Resistant regression and covariance estimation
      modreg       Modern regression: smoothing and local methods
      mva          Classical Multivariate Analysis
+     nlme         Gaussian linear and nonlinear mixed-effects models
      nls          Nonlinear regression
      nnet         Software for feed-forward neural networks with a single
                   hidden layer and for multinomial log-linear models.
      splines      Regression spline functions and classes
      stepfun      Step functions, including empirical distributions
 `.First.lib()' to load compiled code.
    The `man' subdirectory should contain documentation files for the
 objects in the package.  The documentation files to be installed must also
 start with a (lower- or uppercase) letter and have the extension `.Rd' (the
-default) or `.rd'.
+default) or `.rd', and are written in the R documentation format (*note
+Writing R docs: (R-exts)Writing R documentation.)
    C or FORTRAN source and optionally a `Makefile' for the compiled code is
 in `src'.  Note that the `Makefile' most likely is not needed.
    The `data' subdirectory is for additional data files the package makes
 for configuration before installation (such as checking for additional
 software that might be needed by the package), and removing the files
 created in this process.  See the add-on package *e1071* on CRAN for an
 example of this mechanism.
-   See the documentation for `library()' for more information.
+   *Note Creating R pkgs: (R-exts)Creating R packages, for more information.
    The web page `http://www.biostat.washington.edu/~thomas/Rlib.html'
 maintained by Thomas Lumley provides information on porting S packages to R.
    *Note What is CRAN?::, for information on uploading a package to CRAN.
    There is an Emacs package which provides a standard interface between
 statistical programs and statistical processes called ESS ("Emacs Speaks
 Statistics").  It is intended to provide assistance for interactive
 statistical programming and data analysis.  Languages supported include: S
 dialects (S 3/4, S-PLUS 3.x/4.x/5.x, and R), LispStat dialects (XLispStat,
-ViSta), SAS, Stata, SPSS dialects (SPSS, Fiasco) and SCA.
+ViSta), SAS, Stata, SPSS dialects (SPSS, PSPP) and SCA.
    ESS grew out of the desire for bug fixes and extensions to S-mode 4.8
 (which was a GNU Emacs interface to S/S-PLUS version 3 only).  The current
 set of developers desired support for XEmacs, R, S4, and MS Windows.  In
 addition, with new modes being developed for R, Stata, and SAS, it was felt
 .3 Debugging R from within Emacs
 =================================
    To debug R "from within Emacs", there are several possibilities.  To use
+the Emacs GUD (Grand Unified Debugger) library with the recommended
-GUD mode, type `M-x gdb' and give the path to the R _binary_, typically
+debugger GDB, type `M-x gdb' and give the path to the R _binary_, typically
 `R.X11', as argument.  At the gdb prompt, set `R_HOME' and other
 environment variables as needed (using e.g.  `set env R_HOME /path/to/R/',
 but see also below), and start the binary with the desired arguments (e.g.,
-`r --vsize 12M').
+`run --vsize 12M').
    If you have ESS, you can do `C-u M-x R<RET>-d gdb' to start an inferior
 R process with arguments `-d gdb'.
    A third option is to start an inferior R process via ESS (`M-x R') and
 facilities, such as object-name completion, that we know and love.
    When using GUD mode for debugging from within Emacs, you may find it
 most convenient to use the directory with your code in it as the current
 working directory and then make a symbolic link from that directory to the
-R executable.  That way `.gdbinit' can stay in the directory with the code
+R binary.  That way `.gdbinit' can stay in the directory with the code and
-and be used to set up the environment and the search paths for the source,
+be used to set up the environment and the search paths for the source, e.g.
-e.g. as follows:
+as follows:
      set env R_HOME /opt/R
      set env R_PAPERSIZE letter
      set env R_PRINTCMD lpr
      dir /opt/R/src/appl
 ==================
    If R executes an illegal instruction, or dies with an operating system
 error message that indicates a problem in the program (as opposed to
 something like "disk full"), then it is certainly a bug.  If you call
-`.Internal()', `.External()', `.C()' or `.Fortran()' yourself (or in a
+`.C()', `.Fortran()', `.External()' or `.Call()' (or `.Internal()')
-function you wrote), you can always crash R by using wrong argument types
+yourself (or in a function you wrote), you can always crash R by using
-(modes).  This is not a bug.
+wrong argument types (modes).  This is not a bug.
    Taking forever to complete a command can be a bug, but you must make
 certain that it was really R's fault.  Some commands simply take a long
 time.  If the input was such that you _know_ it should have been processed
 quickly, report a bug.  If you don't know whether the command should take a

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