Wed, 20 Dec 2017

Package rstan updated to version 2.17.2 with previous version 2.16.2 dated 2017-07-03

Title: R Interface to Stan
Description: User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Author: Jiqiang Guo [aut], Jonah Gabry [aut], Ben Goodrich [cre, aut], Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Trustees of Columbia University [cph], Oleg Sklyar [cph] (R/cxxfunplus.R), The R Core Team [cph] (R/pairs.R, R/dynGet.R), Jens Oehlschlaegel-Akiyoshi [cph] (R/pairs.R), Hadley Wickham [cph] (R/rtools.R), Joel de Guzman [cph] (Boost), John Fletcher [cph] (Boost), Thomas Heller [cph] (Boost), Eric Niebler [cph] (Boost)
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

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Package remotes updated to version 1.1.1 with previous version 1.1.0 dated 2017-07-09

Title: R Package Installation from Remote Repositories, Including 'GitHub'
Description: Download and install R packages stored in 'GitHub', 'BitBucket', or plain 'subversion' or 'git' repositories. This package is a lightweight replacement of the 'install_*' functions in 'devtools'. Indeed most of the code was copied over from 'devtools'.
Author: Gábor Csárdi [aut, cre], Hadley Wickham [aut], Winston Chang [aut], Jim Hester [aut], RStudio [cph], Martin Morgan [aut], Dan Tenenbaum [aut], Mango Solutions [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package NetworkToolbox updated to version 0.0.1.1 with previous version 0.0.1.0 dated 2017-11-02

Title: Network Filtering Methods and Measures
Description: Implements Information Filtering Networks (IFN; Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), ECO (ECO; Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>), and regression-based filtering network approaches (including the dependency network approach; Kenett, Tumminello, Madi, Gur-Gershogoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>). Also implements several network measures like local network characteristics (e.g., centralities), global network characteristics (e.g., clustering coefficient), and edge replication (Rubinov & Sporns, 2010 <doi:10.1016/j.neuroimage.2009.10.003>). Finally, there are a few bootstrapping techniques that are aimed at increasing the reliability and reproducibility of network analysis (Tumminello, Coronnello, & Lillo, 2007 <doi:10.1142/S0218127407018415>).
Author: Alexander Christensen
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>

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Package mdsr updated to version 0.1.5 with previous version 0.1.4 dated 2017-07-24

Title: Complement to 'Modern Data Science with R'
Description: A complement to *Modern Data Science with R* (ISBN: 978-1498724487, publisher URL: <https://www.crcpress.com/Modern-Data-Science-with-R/Baumer-Kaplan-Horton/p/book/9781498724487>). This package contains all of the data and code necessary to complete exercises and reproduce examples from the text. It also facilitates connections to the SQL database server used in the book.
Author: Ben Baumer [aut, cre], Nicholas Horton [aut], Daniel Kaplan [aut]
Maintainer: Ben Baumer <ben.baumer@gmail.com>

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Package pinbasic updated to version 1.2.0 with previous version 1.1.0 dated 2017-03-02

Title: Fast and Stable Estimation of the Probability of Informed Trading (PIN)
Description: Utilities for fast and stable estimation of the probability of informed trading (PIN) in the model introduced by Easley et al. (2002) <DOI:10.1111/1540-6261.00493> are implemented. Since the basic model developed by Easley et al. (1996) <DOI:10.1111/j.1540-6261.1996.tb04074.x> is nested in the former due to equating the intensity of uninformed buys and sells, functions can also be applied to this simpler model structure, if needed. State-of-the-art factorization of the model likelihood function as well as most recent algorithms for generating initial values for optimization routines are implemented. In total, two likelihood factorizations and three methodologies for starting values are included. Furthermore, functions for simulating datasets of daily aggregated buys and sells, calculating confidence intervals for the probability of informed trading and posterior probabilities of trading days' conditions are available.
Author: Andreas Recktenwald [aut, cre]
Maintainer: Andreas Recktenwald <a.recktenwald@mx.uni-saarland.de>

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Package memisc updated to version 0.99.14.9 with previous version 0.99.14.7 dated 2017-12-04

Title: Management of Survey Data and Presentation of Analysis Results
Description: An infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) 'SPSS' and 'Stata' files is provided. Further, the package allows to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates, which can be exported to 'LaTeX' and HTML.
Author: Martin Elff (with contributions from Christopher N. Lawrence, Dave Atkins, Jason W. Morgan, Achim Zeileis)
Maintainer: Martin Elff <memisc@elff.eu>

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Package kgc updated to version 1.0.0.2 with previous version 1.0.0.1 dated 2017-11-20

Title: Koeppen-Geiger Climatic Zones
Description: Aids in identifying the Koeppen-Geiger (KG) climatic zone for a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system to classify regions of the earth by their relative heat and humidity through the year, for the benefit of human health, plant and agriculture and other human activity [1]. This climate zone classification system, applicable to all of the earths surface, has continued to be developed by scientists up to the present day. Recently one of use (FZ) has published updated, higher accuracy KG climate zone definitions [2]. In this package we use these updated high-resolution maps as the data source [3]. We provide functions that return the KG climate zone for a given longitude and lattitude, or for a given United States zip code. In addition the CZUncertainty() function will check climate zones nearby to check if the given location is near a climate zone boundary. In addition an interactive shiny app is provided to define the KG climate zone for a given longitude and lattitude, or United States zip code. Digital data, as well as animated maps, showing the shift of the climate zones are provided on the following website <http://koeppen-geiger.vu-wien.ac.at>. This work was supported by the DOE-EERE SunShot award DE-EE-0007140. [1] W. Koeppen, (2011) <doi:10.1127/0941-2948/2011/105>. [2] F. Rubel and M. Kottek, (2010) <doi:10.1127/0941-2948/2010/0430>. [3] F. Rubel, K. Brugger, K. Haslinger, and I. Auer, (2016) <doi:10.1127/metz/2016/0816>.
Author: Chelsey Bryant [aut, cre] (0000-0003-3603-4854), Nicholas R. Wheeler [aut] (0000-0003-2248-8919), Franz Rubel [aut] (0000-0002-0048-7379), Roger H. French [aut] (0000-0002-6162-0532)
Maintainer: Chelsey Bryant <clb117@case.edu>

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Package HMP updated to version 1.5.1 with previous version 1.5 dated 2017-07-08

Title: Hypothesis Testing and Power Calculations for Comparing Metagenomic Samples from HMP
Description: Using Dirichlet-Multinomial distribution to provide several functions for formal hypothesis testing, power and sample size calculations for human microbiome experiments.
Author: Patricio S. La Rosa, Elena Deych, Sharina Carter, Berkley Shands, William D. Shannon
Maintainer: Berkley Shands <rpackages@biorankings.com>

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Package ecm updated to version 3.0.0 with previous version 2.0.0 dated 2017-04-01

Title: Build Error Correction Models
Description: Functions for easy building of error correction models (ECM) for time series regression.
Author: Gaurav Bansal
Maintainer: Gaurav Bansal <gaurbans@gmail.com>

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Package bhm updated to version 1.13 with previous version 1.11 dated 2017-05-11

Title: Biomarker Threshold Models
Description: Contains tools to fit both predictive and prognostic biomarker effects using biomarker threshold models. Evaluate the treatment effect, biomarker effect and treatment-biomarker interaction using probability index measurement. Test for treatment-biomarker interaction using residual bootstrap method.
Author: Bingshu E. Chen
Maintainer: Bingshu E. Chen <bingshu.chen@queensu.ca>

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Package picasso updated to version 1.2.0 with previous version 1.0.1 dated 2017-07-20

Title: Pathwise Calibrated Sparse Shooting Algorithm
Description: Computationally efficient tools for fitting generalized linear models and square root loss linear model with convex or non-convex penalty. Users can enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which has significantly less estimation error and overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation and the PathwIse CAlibrated Sparse Shooting algOrithm (PICASSO) which exploits warm start initialization, active set updating, and strong rule for coordinate preselection to boost computation, and attains a linear convergence to a unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using the sparse matrix output.
Author: Jason Ge, Xingguo Li, Mengdi Wang, Tong Zhang, Han Liu and Tuo Zhao
Maintainer: Jason Ge <jiange@princeton.edu>

Diff between picasso versions 1.0.1 dated 2017-07-20 and 1.2.0 dated 2017-12-20

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Package MCDA updated to version 0.0.18 with previous version 0.0.17 dated 2017-09-08

Title: Functions to Support the Multicriteria Decision Aiding Process
Description: Functions which can be useful to support the analyst in the Multicriteria Decision Aiding (MCDA) process involving multiple, conflicting criteria.
Author: Patrick Meyer, Sébastien Bigaret, Richard Hodgett, Alexandru-Liviu Olteanu
Maintainer: Patrick Meyer <patrick.meyer@telecom-bretagne.eu>

Diff between MCDA versions 0.0.17 dated 2017-09-08 and 0.0.18 dated 2017-12-20

 DESCRIPTION                                      |    8 
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 NAMESPACE                                        |    3 
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Package lhs updated to version 0.15 with previous version 0.14 dated 2016-08-09

Title: Latin Hypercube Samples
Description: Provides a number of methods for creating and augmenting Latin Hypercube Samples.
Author: Rob Carnell [aut, cre]
Maintainer: Rob Carnell <bertcarnell@gmail.com>

Diff between lhs versions 0.14 dated 2016-08-09 and 0.15 dated 2017-12-20

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Package dfoptim updated to version 2017.12-1 with previous version 2016.7-1 dated 2016-07-10

Title: Derivative-Free Optimization
Description: Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
Author: Ravi Varadhan, Johns Hopkins University, and Hans W. Borchers, ABB Corporate Research.
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

Diff between dfoptim versions 2016.7-1 dated 2016-07-10 and 2017.12-1 dated 2017-12-20

 DESCRIPTION |    8 ++++----
 MD5         |    8 ++++----
 NEWS        |    3 +++
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 5 files changed, 13 insertions(+), 10 deletions(-)

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Package xts updated to version 0.10-1 with previous version 0.10-0 dated 2017-07-08

Title: eXtensible Time Series
Description: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
Author: Jeffrey A. Ryan [aut, cph], Joshua M. Ulrich [cre, aut], Ross Bennett [ctb]
Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com>

Diff between xts versions 0.10-0 dated 2017-07-08 and 0.10-1 dated 2017-12-20

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 28 files changed, 756 insertions(+), 319 deletions(-)

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New package theseus with initial version 0.1.0
Package: theseus
Type: Package
Title: Analysis and Visualization Tools for Microbial Community Data
Version: 0.1.0
Authors@R: c( person("Jacob", "Price", email = "jrp355@drexel.edu", role = c("aut")), person("Stephen", "Woloszynek", email = "sw424@drexel.edu", role = c("cre","aut")) )
Description: An approach to the visualization, analysis, and interpretation of (microbial) community composition data, especially those originating from amplicon sequencing. Analysis techniques include constrained and unconstrained ordination and visualizing taxonomic abundances and spatial patterns, among others. Methods intended to assist bioinformaticians and ecologists in selecting read trimming by quality scores and preprocessing/denoising of datasets are also provided.
License: MIT + file LICENSE
URL: http://github.com/EESI/theseus
BugReports: http://github.com/EESI/theseus/issues
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.3.0)
Imports: dplyr, ggplot2 (>= 2.2.1), gridExtra, magrittr (>= 1.5), parallel (>= 3.4.1), phyloseq (>= 1.20.0), ShortRead (>= 1.34.0), splancs, tidyverse (>= 1.1.1), tidyr, vegan (>= 2.3.5), viridis (>= 0.4.0)
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-20 14:50:53 UTC; sw1
Author: Jacob Price [aut], Stephen Woloszynek [cre, aut]
Maintainer: Stephen Woloszynek <sw424@drexel.edu>
Repository: CRAN
Date/Publication: 2017-12-20 16:30:53 UTC

More information about theseus at CRAN
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Package StanHeaders updated to version 2.17.1 with previous version 2.16.0-1 dated 2017-07-03

Title: C++ Header Files for Stan
Description: The C++ header files of the Stan project are provided by this package, but it contains no R code, vignettes, or function documentation. There is a shared object containing part of the 'CVODES' library, but it is not accessible from R. 'StanHeaders' is only useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.
Author: Ben Goodrich [cre, aut], Joshua Pritikin [ctb], Andrew Gelman [aut], Bob Carpenter [aut], Matt Hoffman [aut], Daniel Lee [aut], Michael Betancourt [aut], Marcus Brubaker [aut], Jiqiang Guo [aut], Peter Li [aut], Allen Riddell [aut], Marco Inacio [aut], Mitzi Morris [aut], Jeffrey Arnold [aut], Rob Goedman [aut], Brian Lau [aut], Rob Trangucci [aut], Jonah Gabry [aut], Alp Kucukelbir [aut], Robert Grant [aut], Dustin Tran [aut], Michael Malecki [aut], Yuanjun Gao [aut], Trustees of Columbia University [cph], Lawrence Livermore National Security [cph] (CVODES), The Regents of the University of California [cph] (CVODES), Southern Methodist University [cph] (CVODES)
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

Diff between StanHeaders versions 2.16.0-1 dated 2017-07-03 and 2.17.1 dated 2017-12-20

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 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/create_unit_e_dense_inv_metric.hpp           |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/create_unit_e_diag_inv_metric.hpp            |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/experimental_message.hpp                     |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/read_dense_inv_metric.hpp                    |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/read_diag_inv_metric.hpp                     |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/validate_dense_inv_metric.hpp                |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/services/util/validate_diag_inv_metric.hpp                 |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/variational/families/normal_fullrank.hpp                   |    5 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/variational/families/normal_meanfield.hpp                  |    5 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/variational/print_progress.hpp                             |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/src/stan/version.hpp                                                |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core.hpp                                              |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/fvar.hpp                                         |   32 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_addition.hpp                            |   39 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_division.hpp                            |   43 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_equal.hpp                               |   41 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_greater_than.hpp                        |   43 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_greater_than_or_equal.hpp               |   45 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_less_than.hpp                           |   46 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_less_than_or_equal.hpp                  |   43 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_logical_and.hpp                         |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_logical_or.hpp                          |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_multiplication.hpp                      |   45 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_not_equal.hpp                           |   42 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_subtraction.hpp                         |   37 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_unary_minus.hpp                         |   11 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_unary_not.hpp                           |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/core/operator_unary_plus.hpp                          |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/mat.hpp                                               |    1 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/mat/fun/unit_vector_constrain.hpp                     |   11 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/mat/functor/hessian.hpp                               |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/fwd/scal/fun/inc_beta.hpp                                 |    8 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/memory/stack_alloc.hpp                                    |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/mix/mat/functor/hessian.hpp                               |   43 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/arr/err/check_ordered.hpp                            |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/arr/fun/sum.hpp                                      |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/arr/functor/integrate_ode_rk45.hpp                   |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/err/check_ldlt_factor.hpp                        |   41 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/err/check_ordered.hpp                            |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/append_array.hpp                             |   97 -
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/autocorrelation.hpp                          |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/autocovariance.hpp                           |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/block.hpp                                    |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/cholesky_corr_constrain.hpp                  |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/corr_matrix_free.hpp                         |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/cov_matrix_free_lkj.hpp                      |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/csr_to_dense_matrix.hpp                      |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/cumulative_sum.hpp                           |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/factor_U.hpp                                 |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/factor_cov_matrix.hpp                        |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/get_base1.hpp                                |   17 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/get_base1_lhs.hpp                            |   15 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/make_nu.hpp                                  |   32 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/ordered_constrain.hpp                        |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/ordered_free.hpp                             |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/positive_ordered_constrain.hpp               |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/positive_ordered_free.hpp                    |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/prod.hpp                                     |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/quad_form_diag.hpp                           |    8 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/rank.hpp                                     |   50 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/read_corr_L.hpp                              |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/resize.hpp                                   |   38 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/sd.hpp                                       |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/segment.hpp                                  |   10 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/sort_indices.hpp                             |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/squared_distance.hpp                         |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/sub_col.hpp                                  |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/sub_row.hpp                                  |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/to_array_1d.hpp                              |    8 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/to_array_2d.hpp                              |    5 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/to_row_vector.hpp                            |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/to_vector.hpp                                |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/fun/unit_vector_constrain.hpp                    |   17 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/meta/append_return_type.hpp                      |only
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/meta/length_mvt.hpp                              |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/categorical_logit_lpmf.hpp                  |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/categorical_lpmf.hpp                        |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/dirichlet_lpmf.hpp                          |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/lkj_corr_cholesky_lpdf.hpp                  |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/lkj_corr_lpdf.hpp                           |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/ordered_logistic_rng.hpp                    |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/mat/prob/wishart_lpdf.hpp                            |    2 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/err/check_2F1_converges.hpp                     |   11 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/err/check_3F2_converges.hpp                     |   15 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/acosh.hpp                                   |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/as_bool.hpp                                 |   10 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/asinh.hpp                                   |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/atanh.hpp                                   |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/binary_log_loss.hpp                         |   14 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/choose.hpp                                  |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/corr_constrain.hpp                          |   17 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/corr_free.hpp                               |   11 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/fmax.hpp                                    |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/fmin.hpp                                    |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/grad_reg_inc_gamma.hpp                      |   15 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/identity_free.hpp                           |   13 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/int_step.hpp                                |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/lb_constrain.hpp                            |   30 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/lb_free.hpp                                 |   22 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/logical_negation.hpp                        |   16 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/lub_constrain.hpp                           |   31 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/lub_free.hpp                                |   24 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/positive_constrain.hpp                      |   12 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/positive_free.hpp                           |    7 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/prob_constrain.hpp                          |   22 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/prob_free.hpp                               |   15 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/step.hpp                                    |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/ub_constrain.hpp                            |   29 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/ub_free.hpp                                 |   22 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/fun/value_of.hpp                                |   10 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/meta/include_summand.hpp                        |   23 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/meta/length_mvt.hpp                             |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/bernoulli_logit_lpmf.hpp                   |    5 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/bernoulli_lpmf.hpp                         |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/beta_binomial_lpmf.hpp                     |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/beta_cdf.hpp                               |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/beta_lccdf.hpp                             |    7 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/beta_lcdf.hpp                              |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/beta_lpdf.hpp                              |   12 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/binomial_cdf.hpp                           |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/binomial_lccdf.hpp                         |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/binomial_lcdf.hpp                          |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/binomial_logit_lpmf.hpp                    |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/binomial_lpmf.hpp                          |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/cauchy_cdf.hpp                             |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/cauchy_lccdf.hpp                           |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/cauchy_lcdf.hpp                            |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/cauchy_lpdf.hpp                            |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/chi_square_cdf.hpp                         |    2 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/double_exponential_cdf.hpp                 |    6 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/frechet_cdf.hpp                            |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/frechet_lccdf.hpp                          |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/frechet_lpdf.hpp                           |    8 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/gamma_cdf.hpp                              |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/gamma_lcdf.hpp                             |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/gamma_lpdf.hpp                             |    9 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/gumbel_cdf.hpp                             |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/inv_gamma_cdf.hpp                          |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/inv_gamma_lcdf.hpp                         |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/inv_gamma_lpdf.hpp                         |    8 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/logistic_cdf.hpp                           |    3 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/logistic_lccdf.hpp                         |    2 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/logistic_lpdf.hpp                          |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/lognormal_lcdf.hpp                         |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/lognormal_lpdf.hpp                         |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/normal_cdf.hpp                             |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/normal_lccdf.hpp                           |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/poisson_cdf.hpp                            |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/poisson_lpmf.hpp                           |    3 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/skew_normal_lcdf.hpp                       |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/skew_normal_lpdf.hpp                       |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/student_t_cdf.hpp                          |    6 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/student_t_lccdf.hpp                        |    5 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/prim/scal/prob/uniform_lccdf.hpp                          |    4 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/rev/core.hpp                                              |    2 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/rev/scal/fun/gamma_p.hpp                                  |    5 
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 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/rev/scal/fun/inc_beta.hpp                                 |    4 
 StanHeaders-2.17.1/StanHeaders/inst/include/stan/math/rev/scal/fun/pow.hpp                                      |    9 
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More information about StanHeaders at CRAN
Permanent link

Package qrnn updated to version 2.0.2 with previous version 2.0.1 dated 2017-12-11

Title: Quantile Regression Neural Network
Description: Fit quantile regression neural network models with optional left censoring, partial monotonicity constraints, generalized additive model constraints, and the ability to fit multiple non-crossing quantile functions following Cannon (2011) <doi:10.1016/j.cageo.2010.07.005> and Cannon (2017) <doi:10.17605/OSF.IO/WG7SN>.
Author: Alex J. Cannon
Maintainer: Alex J. Cannon <alex.cannon@canada.ca>

Diff between qrnn versions 2.0.1 dated 2017-12-11 and 2.0.2 dated 2017-12-20

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More information about qrnn at CRAN
Permanent link

Package mongolite updated to version 1.3 with previous version 1.2 dated 2017-04-11

Title: Fast and Simple 'MongoDB' Client for R
Description: High-performance 'MongoDB' client based on 'libmongoc' and 'jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication. The online user manual provides an overview of the available methods in the package: <https://jeroen.github.io/mongolite/>.
Author: Jeroen Ooms [aut, cre], MongoDB, Inc [cph] (Bundled mongo-c-driver, see AUTHORS file)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between mongolite versions 1.2 dated 2017-04-11 and 1.3 dated 2017-12-20

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 mongolite-1.3/mongolite/R/options.R                                          |    2 
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 mongolite-1.3/mongolite/src/bson.c                                           |    4 
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 mongolite-1.3/mongolite/src/bson/bson-config.h                               |   32 
 mongolite-1.3/mongolite/src/bson/bson-context-private.h                      |    3 
 mongolite-1.3/mongolite/src/bson/bson-context.c                              |   28 
 mongolite-1.3/mongolite/src/bson/bson-decimal128.c                           |   19 
 mongolite-1.3/mongolite/src/bson/bson-endian.h                               |    2 
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 mongolite-1.3/mongolite/src/bson/bson-iter.h                                 |   15 
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 mongolite-1.3/mongolite/src/bson/bson-macros.h                               |   62 
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 mongolite-1.3/mongolite/src/bson/bson-stdint.h                               |    2 
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 mongolite-1.3/mongolite/src/bson/bson-string.h                               |    2 
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 mongolite-1.3/mongolite/src/bson/bson-types.h                                |    8 
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Package configr updated to version 0.3.2 with previous version 0.3.1.1 dated 2017-11-21

Title: An Implementation of Parsing and Writing Configuration File (JSON/INI/YAML/TOML)
Description: Implements the JSON, INI, YAML and TOML parser for R setting and writing of configuration file. The functionality of this package is similar to that of package 'config'.
Author: Jianfeng Li [aut, cre]
Maintainer: Jianfeng Li <lee_jianfeng@sjtu.edu.cn>

Diff between configr versions 0.3.1.1 dated 2017-11-21 and 0.3.2 dated 2017-12-20

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Package circlize updated to version 0.4.3 with previous version 0.4.2 dated 2017-11-18

Title: Circular Visualization
Description: Circular layout is an efficient way for the visualization of huge amounts of information. Here this package provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of the package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, it gives users more convenience and freedom to design figures for better understanding complex patterns behind multiple dimensional data.
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>

Diff between circlize versions 0.4.2 dated 2017-11-18 and 0.4.3 dated 2017-12-20

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Package RPostgres updated to version 1.0-4 with previous version 1.0-3 dated 2017-12-06

Title: 'Rcpp' Interface to 'PostgreSQL'
Description: Fully 'DBI'-compliant 'Rcpp'-backed interface to 'PostgreSQL' <https://www.postgresql.org/>, an open-source relational database.
Author: Hadley Wickham [aut], Jeroen Ooms [aut], Kirill Müller [cre], RStudio [cph], R Consortium [cph], Tomoaki Nishiyama [ctb] (Code for encoding vectors into strings derived from RPostgreSQL), Kungliga Tekniska Högskolan [ctb] (Source code for timegm)
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between RPostgres versions 1.0-3 dated 2017-12-06 and 1.0-4 dated 2017-12-20

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Package rFSA updated to version 0.9 with previous version 0.1.0 dated 2016-10-18

Title: Feasible Solution Algorithm for Finding Best Subsets and Interactions
Description: Assists in statistical model building to find optimal and semi-optimal higher order interactions and best subsets. Uses the lm(), glm(), and other R functions to fit models generated from a feasible solution algorithm. Discussed in Subset Selection in Regression, A Miller (2002). Applied and explained for least median of squares in Hawkins (1993) <doi:10.1016/0167-9473(93)90246-P>. The feasible solution algorithm comes up with model forms of a specific type that can have fixed variables, higher order interactions and their lower order terms.
Author: Joshua Lambert [aut, cre], Liyu Gong [aut], Corrine Elliott [ctb], Sarah sawi234@g.uky.edu Janse [ctb]
Maintainer: Joshua Lambert <joshua.lambert@uky.edu>

Diff between rFSA versions 0.1.0 dated 2016-10-18 and 0.9 dated 2017-12-20

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Package fmriqa updated to version 0.2.0 with previous version 0.1.0 dated 2017-11-24

Title: Functional MRI Quality Assurance Routines
Description: Methods for performing fMRI quality assurance (QA) measurements of test objects. Heavily based on the fBIRN procedures detailed by Friedman and Glover (2006) <doi:10.1002/jmri.20583>.
Author: Martin Wilson [cre, aut]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

Diff between fmriqa versions 0.1.0 dated 2017-11-24 and 0.2.0 dated 2017-12-20

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New package datoramar with initial version 0.1.0
Package: datoramar
Type: Package
Title: Interface to the 'Datorama' API
Version: 0.1.0
Authors@R: person("Kade", "Killary", email = "kadekillary@protonmail.com", role = c("aut", "cre"))
URL: https://github.com/beigebrucewayne/datoramar
BugReports: https://github.com/beigebrucewayne/datoramar/issues
Description: A thin wrapper around the 'Datorama' API. Ideal for analyzing marketing data from <https://datorama.com>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, tibble
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-20 04:49:58 UTC; Kade.Killary
Author: Kade Killary [aut, cre]
Maintainer: Kade Killary <kadekillary@protonmail.com>
Repository: CRAN
Date/Publication: 2017-12-20 15:42:51 UTC

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Package nparACT updated to version 0.8 with previous version 0.7 dated 2016-12-23

Title: Non-Parametric Measures of Actigraphy Data
Description: Computes interdaily stability (IS), intradaily variability (IV) & the relative amplitude (RA) from actigraphy data as described in Blume et al. (2016) <doi: 10.1016/j.mex.2016.05.006> and van Someren et al. (1999) <doi: 10.3109/07420529908998724>. Additionally, it also computes L5 (i.e. the 5 hours with lowest average actigraphy amplitude) and M10 (the 10 hours with highest average amplitude) as well as the respective start times. The flex versions will also compute the L-value for a user-defined number of minutes. IS describes the strength of coupling of a rhythm to supposedly stable zeitgebers. It varies between 0 (Gaussian Noise) and 1 for perfect IS. IV describes the fragmentation of a rhythm, i.e. the frequency and extent of transitions between rest and activity. It is near 0 for a perfect sine wave, about 2 for Gaussian noise and may be even higher when a definite ultradian period of about 2 hrs is present. RA is the relative amplitude of a rhythm. Note that to obtain reliable results, actigraphy data should cover a reasonable number of days.
Author: Christine Blume <christine.blume@sbg.ac.at> Nayantara Santhi <n.santhi@surrey.ac.uk> Manuel Schabus <manuel.schabus@sbg.ac.at>
Maintainer: Christine Blume <christine.blume@sbg.ac.at>

Diff between nparACT versions 0.7 dated 2016-12-23 and 0.8 dated 2017-12-20

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New package tfestimators with initial version 1.4.2
Package: tfestimators
Type: Package
Title: Interface to 'TensorFlow' Estimators
Version: 1.4.2
Authors@R: c( person("JJ", "Allaire", role = c("aut", "cre"), email = "jj@rstudio.com"), person("Yuan", "Tang", role = c("aut"), email = "terrytangyuan@gmail.com"), person("Kevin", "Ushey", role = c("aut"), email = "kevin@rstudio.com"), person("Kevin", "Kuo", role = c("aut"), email = "kevin.kuo@rstudio.com"), person("Daniel", "Falbel", role = c("ctb", "cph")), person("RStudio", role = c("cph", "fnd")), person(family = "Google Inc.", role = c("cph")) )
Description: Interface to 'TensorFlow' Estimators <https://www.tensorflow.org/programmers_guide/estimators>, a high-level API that provides implementations of many different model types including linear models and deep neural networks.
License: Apache License 2.0
URL: https://github.com/rstudio/tfestimators
BugReports: https://github.com/rstudio/tfestimators/issues
SystemRequirements: TensorFlow (https://www.tensorflow.org/)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1)
Imports: magrittr, progress, reticulate (>= 1.3.1), rlang, tensorflow (>= 1.4.2), tfruns (>= 1.1), tidyselect, utils, purrr, tibble, tidyr
RoxygenNote: 6.0.1
Suggests: ggplot2, modelr (>= 0.1.1), testthat, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-20 11:43:28 UTC; jjallaire
Author: JJ Allaire [aut, cre], Yuan Tang [aut], Kevin Ushey [aut], Kevin Kuo [aut], Daniel Falbel [ctb, cph], RStudio [cph, fnd], Google Inc. [cph]
Maintainer: JJ Allaire <jj@rstudio.com>
Repository: CRAN
Date/Publication: 2017-12-20 13:19:50 UTC

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Package MonoPoly updated to version 0.3-9 with previous version 0.3-8 dated 2016-04-05

Title: Functions to Fit Monotone Polynomials
Description: Functions for fitting monotone polynomials to data. Detailed discussion of the methodologies used can be found in Murray, Mueller and Turlach (2013) <doi:10.1007/s00180-012-0390-5> and Murray, Mueller and Turlach (2016) <doi:10.1080/00949655.2016.1139582>.
Author: Berwin A. Turlach [aut, cre] (0000-0001-8795-471X), Kevin Murray [ctb] (0000-0002-8856-6046)
Maintainer: Berwin A. Turlach <Berwin.Turlach@gmail.com>

Diff between MonoPoly versions 0.3-8 dated 2016-04-05 and 0.3-9 dated 2017-12-20

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Package GAS updated to version 0.2.6 with previous version 0.2.5 dated 2017-11-17

Title: Generalized Autoregressive Score Models
Description: Simulate, estimate and forecast using univariate and multivariate GAS models as described in Ardia et al. (2016) <https://ssrn.com/abstract=2825380>.
Author: Leopoldo Catania [aut,cre], Kris Boudt [ctb], David Ardia [ctb]
Maintainer: Leopoldo Catania <leopoldo.catania@econ.au.dk>

Diff between GAS versions 0.2.5 dated 2017-11-17 and 0.2.6 dated 2017-12-20

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New package sparseEigen with initial version 0.1.0
Package: sparseEigen
Title: Computation of Sparse Eigenvectors of a Matrix
Version: 0.1.0
Description: Computation of sparse eigenvectors of a matrix (aka sparse PCA) with running time 2-3 orders of magnitude lower than existing methods and better final performance in terms of recovery of sparsity pattern and estimation of numerical values. Can handle covariance matrices as well as data matrices with real or complex-valued entries. Different levels of sparsity can be specified for each individual ordered eigenvector and the method is robust in parameter selection. See vignette for a detailed documentation and comparison, with several illustrative examples. The package is based on the paper: K. Benidis, Y. Sun, P. Babu, and D. P. Palomar (2016). "Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation," IEEE Transactions on Signal Processing <doi:10.1109/TSP.2016.2605073>.
Authors@R: c( person("Konstantinos", "Benidis", role = "aut", email = "benidisk@gmail.com"), person("Daniel", "Palomar", middle = "P.", role = c("cre", "aut"), email = "daniel.p.palomar@gmail.com") )
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>
URL: https://github.com/dppalomar/sparseEigen, https://www.danielppalomar.com, https://doi.org/10.1109/TSP.2016.2605073
BugReports: https://github.com/dppalomar/sparseEigen/issues
Depends: R (>= 3.4.0)
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
Imports:
RoxygenNote: 6.0.1
Suggests: knitr, MASS, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-20 08:57:59 UTC; palomar
Author: Konstantinos Benidis [aut], Daniel P. Palomar [cre, aut]
Repository: CRAN
Date/Publication: 2017-12-20 12:57:21 UTC

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New package SimCop with initial version 0.7.0
Package: SimCop
Type: Package
Title: Simulate from Arbitrary Copulae
Version: 0.7.0
Date: 2017-12-16
Authors@R: c(person(c("Berwin", "A."), "Turlach", role=c("aut", "cre"), email="Berwin.Turlach@gmail.com"), person("Nader", "Tajvidi", role="ctb", email="Nader.Tajvidi@matstat.lu.se"))
Description: Provides a framework to generating random variates from arbitrary multivariate copulae, while concentrating on (bivariate) extreme value copulae. Particularly useful if the multivariate copulae are not available in closed form.
Depends: R (>= 3.4.0)
Imports: grDevices, graphics, quadprog, stats
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-16 08:32:11 UTC; berwin
Author: Berwin A. Turlach [aut, cre], Nader Tajvidi [ctb]
Maintainer: Berwin A. Turlach <Berwin.Turlach@gmail.com>
Repository: CRAN
Date/Publication: 2017-12-20 12:07:17 UTC

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New package OGI with initial version 1.0.0
Package: OGI
Type: Package
Title: Objective General Index
Version: 1.0.0
Authors@R: c( person("Tomonari", "Sei", email = "sei@mist.i.u-tokyo.ac.jp", role = "aut"), person("Masaki", "Hamada", email = "masaki_hamada@mist.i.u-tokyo.ac.jp", role = "cre"))
Description: Consider a data matrix of n individuals with p variates. The objective general index (OGI) is a general index that combines the p variates into a univariate index in order to rank the n individuals. The OGI is always positively correlated with each of the variates. More details can be found in Sei (2016) <doi:10.1016/j.jmva.2016.02.005>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: lpSolve (>= 5.6.13), stats (>= 3.3.3), graphics (>= 3.3.3), methods (>= 3.3.3)
Suggests: ade4 (>= 1.7.8), bnlearn (>= 4.2), testthat(>= 1.0.2)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-20 01:53:57 UTC; MEIP-users
Author: Tomonari Sei [aut], Masaki Hamada [cre]
Maintainer: Masaki Hamada <masaki_hamada@mist.i.u-tokyo.ac.jp>
Repository: CRAN
Date/Publication: 2017-12-20 12:38:57 UTC

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New package gllvm with initial version 0.1.0
Package: gllvm
Type: Package
Title: Generalized Linear Latent Variable Models
Version: 0.1.0
Author: Jenni Niku, Wesley Brooks, Riki Herliansyah, Francis K.C. Hui, Sara Taskinen, David I. Warton
Maintainer: Jenni Niku <jenni.m.e.niku@jyu.fi>
Description: Generalized linear latent variable model (gllvm) for analyzing multivariate data. Estimation is performed using either Laplace approximation or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>). Details for gllvm, see Hui et al. (2015) <doi:10.1111/2041-210X.12236> and (2017) <doi:10.1080/10618600.2016.1164708> and Niku et al. (2017) <doi:10.1007/s13253-017-0304-7>.
License: GPL-2
Imports: Rcpp (>= 0.12.11), MASS, Matrix, mvtnorm, statmod, fishMod
Depends: TMB, mvabund
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, TMB, RcppEigen
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-12-19 20:44:05 UTC; Jenni
Repository: CRAN
Date/Publication: 2017-12-20 12:02:54 UTC

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Package dLagM updated to version 1.0.0 with previous version 0.1.0 dated 2017-09-11

Title: Time Series Regression Models with Distributed Lag Models
Description: Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Baltagi (2011) <doi:10.1007/978-3-642-20059-5> for more information.
Author: Haydar Demirhan
Maintainer: Haydar Demirhan <haydar.demirhan@rmit.edu.au>

Diff between dLagM versions 0.1.0 dated 2017-09-11 and 1.0.0 dated 2017-12-20

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Package BayesianTools updated to version 0.1.4 with previous version 0.1.3 dated 2017-08-02

Title: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics
Description: General-purpose MCMC and SMC samplers, as well as plot and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.
Author: Florian Hartig [aut, cre], Francesco Minunno [aut], Stefan Paul [aut], David Cameron [ctb], Tankred Ott [ctb]
Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de>

Diff between BayesianTools versions 0.1.3 dated 2017-08-02 and 0.1.4 dated 2017-12-20

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New package SPCAvRP with initial version 0.1
Package: SPCAvRP
Type: Package
Title: Sparse Principal Component Analysis via Random Projections (SPCAvRP)
Version: 0.1
Date: 2017-12-19
Author: Milana Gataric, Tengyao Wang and Richard J. Samworth
Maintainer: Milana Gataric <m.gataric@statslab.cam.ac.uk>
Description: Implements the SPCAvRP algorithm, developed and analysed in "Sparse principal component analysis via random projections" Gataric, M., Wang, T. and Samworth, R. J. (2017) <arXiv:1712.05630>. The algorithm is based on the aggregation of eigenvector information from carefully-selected random projections of the sample covariance matrix.
Depends: R (>= 3.0.0), parallel, MASS
License: GPL-3
URL: https://arxiv.org/abs/1712.05630
NeedsCompilation: no
Repository: CRAN
Packaged: 2017-12-19 20:03:26 UTC; mg617
RoxygenNote: 6.0.1
Date/Publication: 2017-12-20 10:51:07 UTC

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Package rxylib updated to version 0.2.1 with previous version 0.2.0 dated 2017-07-27

Title: Import XY-Data into R
Description: Provides access to the 'xylib' C library for to import xy data from powder diffraction, spectroscopy and other experimental methods.
Author: Sebastian Kreutzer [aut, trl, cre], Johannes Friedrich [aut], RLum Team [ctb], Marcin Wojdyr [cph] (C++ library 'xylib'), Peng Zhang [cph] (C++ library 'xylib')
Maintainer: Sebastian Kreutzer <sebastian.kreutzer@u-bordeaux-montaigne.fr>

Diff between rxylib versions 0.2.0 dated 2017-07-27 and 0.2.1 dated 2017-12-20

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Package inpdfr updated to version 0.1.6 with previous version 0.1.5 dated 2017-02-27

Title: Analyse Text Documents Using Ecological Tools
Description: A set of functions to analyse and compare texts, using classical text mining functions, as well as those from theoretical ecology.
Author: Rebaudo Francois (IRD, UMR EGCE, Univ.ParisSud-CNRS-IRD- Univ.ParisSaclay)
Maintainer: Rebaudo Francois <francois.rebaudo@ird.fr>

Diff between inpdfr versions 0.1.5 dated 2017-02-27 and 0.1.6 dated 2017-12-20

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Package dataPreparation updated to version 0.3.4 with previous version 0.3.2 dated 2017-10-25

Title: Automated Data Preparation
Description: Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of data.table efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
Author: Emmanuel-Lin Toulemonde [aut, cre]
Maintainer: Emmanuel-Lin Toulemonde <el.toulemonde@protonmail.com>

Diff between dataPreparation versions 0.3.2 dated 2017-10-25 and 0.3.4 dated 2017-12-20

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New package bcmaps with initial version 0.16.0
Package: bcmaps
Title: Map Layers and Spatial Utilities for British Columbia
Version: 0.16.0
Date: 2017-12-08
Authors@R: c(person("Andy", "Teucher", email = "andy.teucher@gov.bc.ca", role = c("aut", "cre")), person("Stephanie", "Hazlitt", email = "stephanie.hazlitt@gov.bc.ca", role = "aut"), person("Sam", "Albers", email = "sam.albers@gov.bc.ca", role = "aut"), person("Province of British Columbia", role="cph"))
Description: Provides access to various spatial layers for B.C., such as administrative boundaries, natural resource management boundaries, etc. All layers are imported from the 'bcmaps.rdata' package as 'sf' or 'Spatial' objects through function calls in this package. All layers are in B.C. 'Albers' projection <http://spatialreference.org/ref/epsg/nad83-bc-albers/>, which is the B.C. government standard <https://www.for.gov.bc.ca/hts/risc/pubs/other/mappro/index.htm>.
Depends: R (>= 3.4.0)
Imports: methods, utils, stats, sf (>= 0.5-4), rappdirs (>= 0.3.1), httr (>= 1.3.1)
License: Apache License (== 2.0) | file LICENSE
LazyData: true
RoxygenNote: 6.0.1
Suggests: bcmaps.rdata (>= 0.1.3), knitr, rmarkdown, sp (>= 1.2-5), rgdal (>= 1.2-13), rgeos (>= 0.3-25), raster (>= 2.5-8), ggplot2 (>= 2.2.1), glue (>= 1.1.1), doMC (>= 1.3.4), plyr (>= 1.8.4), testthat
Additional_repositories: https://bcgov.github.io/drat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-15 21:40:21 UTC; ateucher
Author: Andy Teucher [aut, cre], Stephanie Hazlitt [aut], Sam Albers [aut], Province of British Columbia [cph]
Maintainer: Andy Teucher <andy.teucher@gov.bc.ca>
Repository: CRAN
Date/Publication: 2017-12-20 09:57:47 UTC

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Package rmonad updated to version 0.4.0 with previous version 0.3.0 dated 2017-10-05

Title: A Monadic Pipeline System
Description: A monadic solution to pipeline analysis. All operations -- and the errors, warnings and messages they emit -- are merged into a directed graph. Infix binary operators mediate when values are stored, how exceptions are handled, and where pipelines branch and merge. The resulting structure may be queried for debugging or report generation. 'rmonad' complements, rather than competes with, non-monadic pipeline packages like 'magrittr' or 'pipeR'. This work is funded by the NSF (award number 1546858).
Author: Zebulun Arendsee [aut, cre]
Maintainer: Zebulun Arendsee <zbwrnz@gmail.com>

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 112 files changed, 2473 insertions(+), 1297 deletions(-)

More information about rmonad at CRAN
Permanent link

Package AnthropMMD updated to version 2.3.3 with previous version 2.3.2 dated 2017-12-04

Title: An R-Shiny Application for Smith's Mean Measure of Divergence (MMD)
Description: Offers a Shiny user interface for the calculation of the mean measure of divergence, with facilities for trait selection and graphical representations.
Author: Frederic Santos
Maintainer: Frederic Santos <frederic.santos@u-bordeaux.fr>

Diff between AnthropMMD versions 2.3.2 dated 2017-12-04 and 2.3.3 dated 2017-12-20

 DESCRIPTION                          |    8 ++++----
 MD5                                  |   16 ++++++++--------
 inst/AnthropMMDShinyApp/calcIMD.R    |    8 ++++----
 inst/AnthropMMDShinyApp/selectVars.R |    6 +++---
 inst/AnthropMMDShinyApp/server.R     |    8 ++++----
 inst/AnthropMMDShinyApp/ui.R         |    5 ++++-
 inst/CITATION                        |    7 +++++--
 man/AnthropMMD-package.Rd            |   12 ++++++------
 man/StartMMD.Rd                      |   10 +++++-----
 9 files changed, 43 insertions(+), 37 deletions(-)

More information about AnthropMMD at CRAN
Permanent link


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