Wed, 20 Jan 2010

Package RWeka updated to version 0.4-1 with previous version 0.3-25 dated 2010-01-18

Title: R/Weka interface
Description: An R interface to Weka (Version 3.7.1). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Both the R interface and Weka itself are contained in the RWeka package. For more information on Weka see http://www.cs.waikato.ac.nz/~ml/weka/.
Author: Kurt Hornik, with contributions from Christian Buchta, Torsten Hothorn, Alexandros Karatzoglou, David Meyer, and Achim Zeileis
Maintainer: Kurt Hornik

Diff between RWeka versions 0.3-25 dated 2010-01-18 and 0.4-1 dated 2010-01-20

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New package umlr with initial version 0.1.1
Package: umlr
Title: Statistical Software Development with UML and R
Depends: oosp (>= 0.2.0)
Version: 0.1.1
Date: 2010-01-20
Author: CHARLOTTE MAIA
Maintainer: Charlotte Maia
Description: Very early and very rough (hence very limited) prototype for developing statistical software with UML and R, with an emphasis on using (both Latex-friendly and GUI-based) UML class diagrams for object oriented design and visualisation.
License: GPL (>= 2)
Packaged: 2010-01-20 08:49:16 UTC; maia
Repository: CRAN
Date/Publication: 2010-01-20 13:11:18

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Package halp updated to version 0.1.3 with previous version 0.1.2 dated 2010-01-18

Title: Show certain type of comments from function bodies as "live-help"
Description: Show certain type of comments from function bodies as "live-help"
Author: Daniel Haase
Maintainer: Daniel Haase

Diff between halp versions 0.1.2 dated 2010-01-18 and 0.1.3 dated 2010-01-20

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Package gRapHD updated to version 0.1.5 with previous version 0.1.4 dated 2010-01-19

Title: Efficient selection of undirected graphical models for high-dimensional datasets
Description: gRapHD is designed for efficient selection of high-dimensional undirected graphical models. The package provides tools for selecting trees, forests and decomposable models minimizing information criteria such as AIC or BIC, and for displaying the independence graphs of the models. It has also some useful tools for analysing graphical structures. It supports the use of discrete, continuous, or both types of variables.
Author: Gabriel Coelho Goncalves de Abreu , Rodrigo Labouriau , David Edwards .
Maintainer: Gabriel Coelho Goncalves de Abreu

Diff between gRapHD versions 0.1.4 dated 2010-01-19 and 0.1.5 dated 2010-01-20

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Package ff updated to version 2.1-2 with previous version 2.1-1 dated 2009-11-05

Title: memory-efficient storage of large data on disk and fast access functions
Description: The ff package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section (pagesize) in main memory - the effective virtual memory consumption per ff object. ff supports R's standard atomic data types 'double', 'logical', 'raw' and 'integer' and non-standard atomic types boolean (1 bit), quad (2 bit unsigned), nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), single (4 byte float with NAs). For example 'quad' allows efficient storage of genomic data as an 'A','T','G','C' factor. The unsigned types support 'circular' arithmetic. There is also support for close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and custom close-to-atomic types. ff not only has native C-support for vectors, matrices and arrays with flexible dimorder (major column-order, major row-order and generalizations for arrays). There is also a ffdf class not unlike data.frames and import/export filters for csv files. ff objects store raw data in binary flat files in native encoding, and complement this with metadata stored in R as physical and virtual attributes. ff objects have well-defined hybrid copying semantics, which gives rise to certain performance improvements through virtualization. ff objects can be stored and reopened across R sessions. ff files can be shared by multiple ff R objects (using different data en/de-coding schemes) in the same process or from multiple R processes to exploit parallelism. A wide choice of finalizer options allows to work with 'permanent' files as well as creating/removing 'temporary' ff files completely transparent to the user. On certain OS/Filesystem combinations, creating the ff files works without notable delay thanks to using sparse file allocation. Several access optimization techniques such as Hybrid Index Preprocessing and Virtualization are implemented to achieve good performance even with large datasets, for example virtual matrix transpose without touching a single byte on disk. Further, to reduce disk I/O, 'logicals' and non-standard data types get stored native and compact on binary flat files i.e. logicals take up exactly 2 bits to represent TRUE, FALSE and NA. Beyond basic access functions, the ff package also provides compatibility functions that facilitate writing code for ff and ram objects and support for batch processing on ff objects (e.g. as.ram, as.ff, ffapply). ff interfaces closely with functionality from package 'bit': chunked looping, fast bit operations and coercions between different objects that can store subscript information ('bit', 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows to work interactively with selections of large datasets and quickly modify selection criteria. Further high-performance enhancements can be made available upon request.
Author: Daniel Adler , Christian Gl\xE4ser , Oleg Nenadic , Jens Oehlschl\xE4gel , Walter Zucchini
Maintainer: Jens Oehlschl\xE4gel

Diff between ff versions 2.1-1 dated 2009-11-05 and 2.1-2 dated 2010-01-20

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Package bit updated to version 1.1-3 with previous version 1.1-2 dated 2009-10-26

Title: A class for vectors of 1-bit booleans
Description: bitmapped vectors of booleans (no NAs), coercion from and to logicals, integers and integer subscripts; fast boolean operators and fast summary statistics. With 'bit' vectors you can store true binary booleans {FALSE,TRUE} at the expense of 1 bit only, on a 32 bit architecture this means factor 32 less RAM and ~ factor 32 more speed on boolean operations. Due to overhead of R calls, actual speed gain depends on the size of the vector: expect gains for vectors of size > 10000 elements. Even for one-time boolean operations it can pay-off to convert to bit, the pay-off is obvious, when such components are used more than once. Reading from and writing to bit is approximately as fast as accessing standard logicals - mostly due to R's time for memory allocation. The package allows to work with pre-allocated memory for return values by calling .Call() directly: when evaluating the speed of C-access with pre-allocated vector memory, coping from bit to logical requires only 70% of the time for copying from logical to logical; and copying from logical to bit comes at a performance penalty of 150%. the package now contains further classes for representing logical selections: 'bitwhich' for very skewed selections and 'ri' for selecting ranges of values for chunked processing. All three index classes can be used for subsetting 'ff' objects (ff-2.1-0 and higher).
Author: Jens Oehlschl\xE4gel
Maintainer: Jens Oehlschl\xE4gel

Diff between bit versions 1.1-2 dated 2009-10-26 and 1.1-3 dated 2010-01-20

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Package PK updated to version 1.2-0 with previous version 1.01 dated 2009-04-30

Title: Basic Non-Compartmental Pharmacokinetics
Description: Estimation of pharmacokinetic parameters using non-compartmental theory
Author: Thomas Jaki and Martin J. Wolfsegger
Maintainer: Thomas Jaki

Diff between PK versions 1.01 dated 2009-04-30 and 1.2-0 dated 2010-01-20

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Package ttrTests updated to version 1.4 with previous version 1.3 dated 2010-01-01

Title: Standard Backtests for Technical Trading Rules in Financial Data
Description: Four core functions evaluate the efficacy of a technical trading rule. - Conditional return statistics - Bootstrap resampling statistics - Reality Check for data snooping bias among parameter choices - Robustness, or Persistence, of parameter choices
Author: David St John
Maintainer: David St John

Diff between ttrTests versions 1.3 dated 2010-01-01 and 1.4 dated 2010-01-20

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Package survey updated to version 3.19 with previous version 3.18 dated 2009-09-22

Title: analysis of complex survey samples
Description: Summary statistics, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. Predictive margins by direct standardization. PPS sampling without replacement.
Author: Thomas Lumley
Maintainer: Thomas Lumley

Diff between survey versions 3.18 dated 2009-09-22 and 3.19 dated 2010-01-20

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Package nnclust updated to version 2.2 with previous version 2.1 dated 2009-09-22

Title: Nearest-neighbour tools for clustering
Description: Finds nearest neighours and the minimum spanning tree for large data sets, does clustering using the minimum spanning tree.
Author: Thomas Lumley
Maintainer: Thomas Lumley

Diff between nnclust versions 2.1 dated 2009-09-22 and 2.2 dated 2010-01-20

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Package mvabund updated to version 0.1-7 with previous version 0.1-6 dated 2010-01-14

Title: statistical methods for analysing multivariate abundance data
Description: A set of tools for displaying, modeling and analysing multivariate abundance data in community ecology. See mvabund-package.Rd for details of overall package organization. The package is implemented with the Gnu Scientific Library (http://www.gnu.org/software/gsl/) and Rcpp (http://dirk.eddelbuettel.com/code/rcpp.html) R / C++ classes.
Author: Ulrike Naumann, Yi Wang and David Warton
Maintainer: Yi Wang

Diff between mvabund versions 0.1-6 dated 2010-01-14 and 0.1-7 dated 2010-01-20

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Package mecdf updated to version 0.3.1 with previous version 0.3.0 dated 2010-01-11

Title: Multivariate ECDF-Based Models
Description: Univariate and multivariate empirical cumulative distribution functions (ECDFs), including both step functions (true ECDFs) and continuous functions (via interpolation). Plus special purpose functions for plotting univariate and bivariate ECDFs.
Author: CHARLOTTE MAIA
Maintainer: Charlotte Maia

Diff between mecdf versions 0.3.0 dated 2010-01-11 and 0.3.1 dated 2010-01-20

 DESCRIPTION        |   10 +++++-----
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Package RLRsim updated to version 2.0-4 with previous version 2.0-2 dated 2008-08-12

Title: Exact (Restricted) Likelihood Ratio tests for mixed and additive models.
Description: Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(),lme4::lmer(), mgcv::gamm() and SemiPar:spm()
Author: Fabian Scheipl
Maintainer: Fabian Scheipl

Diff between RLRsim versions 2.0-2 dated 2008-08-12 and 2.0-4 dated 2010-01-20

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Package GRASS updated to version 0.3-9 with previous version 0.3-8 dated 2009-09-18

Title: Interface between GRASS 5.0 geographical information system and R
Description: Interface between GRASS 5.0 geographical information system and R, based on starting R from within the GRASS environment using values of environment variables set in the GISRC file. Interface examples should be run outside GRASS, others may be run within. Wrapper and helper functions are provided for a range of R functions to match the interface metadata structures.
Author: Roger Bivand
Maintainer: Roger Bivand

Diff between GRASS versions 0.3-8 dated 2009-09-18 and 0.3-9 dated 2010-01-20

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Package GLDEX updated to version 1.0.4.1 with previous version 1.0.3.4 dated 2009-11-09

Title: Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods
Description: The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution.
Author: Steve Su
Maintainer: Steve Su

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 R/fun.fit.gl.v4a.R                  |only
 R/fun.fit.gl.v6.R                   |only
 R/fun.fit.gl.v6a.R                  |only
 R/fun.fmkl.mm.sol.R                 |    2 
 R/fun.fmkl.mm.sol.alt.R             |    4 -
 R/fun.lambda.percentile.R           |    2 
 R/fun.lm.theo.gld.R                 |only
 R/fun.moments.R                     |   10 +++-
 R/fun.moments.r.R                   |only
 R/fun.plot.fit.bm.R                 |   67 ++++++++++++++++---------------
 R/fun.rs.perc.sol.R                 |    2 
 R/fun.rs.perc.sol.alt.R             |    2 
 R/optim.fun.lm.R                    |only
 R/optim.fun.qs.R                    |only
 R/optim.fun6.R                      |only
 R/optim.fun7.R                      |only
 R/skewness.R                        |    3 -
 R/starship.R                        |    7 ++-
 R/t1lmoments.R                      |only
 man/FMKLfittingandbasicfunctions.Rd |    1 
 man/GLDEX.package.Rd                |   77 +++++++++++++++++++++++++++++-------
 man/Lmoments.Rd                     |only
 man/RSfittingandbasicfunctions.Rd   |    1 
 man/fittingfunctions.Rd             |    7 +++
 man/fun.RMFMKL.hs.Rd                |    2 
 man/fun.RMFMKL.hs.nw.Rd             |    2 
 man/fun.RMFMKL.lm.Rd                |only
 man/fun.RMFMKL.ml.Rd                |    5 +-
 man/fun.RMFMKL.mm.Rd                |only
 man/fun.RMFMKL.qs.Rd                |only
 man/fun.RPRS.hs.Rd                  |    2 
 man/fun.RPRS.hs.nw.Rd               |    2 
 man/fun.RPRS.lm.Rd                  |only
 man/fun.RPRS.ml.Rd                  |    5 +-
 man/fun.RPRS.mm.Rd                  |only
 man/fun.RPRS.qs.Rd                  |only
 man/fun.auto.bimodal.ml.Rd          |   15 +++----
 man/fun.auto.bimodal.pml.Rd         |   13 ++----
 man/fun.auto.bimodal.qs.Rd          |only
 man/fun.data.fit.hs.Rd              |    2 
 man/fun.data.fit.hs.nw.Rd           |    2 
 man/fun.data.fit.lm.Rd              |only
 man/fun.data.fit.ml.Rd              |    9 ++--
 man/fun.data.fit.mm.Rd              |only
 man/fun.data.fit.qs.Rd              |only
 man/fun.gen.qrn.Rd                  |    6 --
 man/fun.lm.theo.gld.Rd              |only
 man/fun.moments.bimodal.Rd          |    4 -
 man/fun.moments.r.Rd                |only
 man/fun.theo.mv.gld.Rd              |    4 -
 man/optimisationfunctions.Rd        |    4 +
 man/t1lmoments.Rd                   |only
 82 files changed, 220 insertions(+), 125 deletions(-)

More information about GLDEX at CRAN
Permanent link

Package ConvCalendar updated to version 1.1 with previous version 1.0 dated 2009-01-08

Title: Converts dates between calendars
Description: Converts between the Date class and d/m/y for several calendars, including Persian, Islamic, and Hebrew
Author: Bill J. Gray (www.projectpluto.com/calendar) and Thomas Lumley
Maintainer: Thomas Lumley

Diff between ConvCalendar versions 1.0 dated 2009-01-08 and 1.1 dated 2010-01-20

 ConvCalendar-1.0/ConvCalendar/LICENCE          |only
 ConvCalendar-1.1/ConvCalendar/COPYRIGHTS       |only
 ConvCalendar-1.1/ConvCalendar/DESCRIPTION      |   17 ++++++++++-------
 ConvCalendar-1.1/ConvCalendar/NAMESPACE        |    2 ++
 ConvCalendar-1.1/ConvCalendar/NEWS             |only
 ConvCalendar-1.1/ConvCalendar/R/as.OtherDate.R |    3 +++
 ConvCalendar-1.1/ConvCalendar/man/OtherDate.Rd |   12 +++++++++++-
 7 files changed, 26 insertions(+), 8 deletions(-)

More information about ConvCalendar at CRAN
Permanent link


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