Title: A Statistically Sound 'data.frame' Processor/Conditioner
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner.
'vtreat' prepares variables so that data has fewer exceptional cases, making
it easier to safely use models in production. Common problems 'vtreat' defends
against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new
categorical levels (levels seen during application, but not during training).
'vtreat::prepare' should be used as you would use 'model.matrix'.
Author: John Mount [aut, cre],
Nina Zumel [aut],
Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>
Diff between vtreat versions 1.0.0 dated 2017-10-04 and 1.0.1 dated 2017-10-16
vtreat-1.0.0/vtreat/tests/testthat/testDataTable.R |only vtreat-1.0.1/vtreat/DESCRIPTION | 12 ++-- vtreat-1.0.1/vtreat/MD5 | 33 +++++------ vtreat-1.0.1/vtreat/NEWS.md | 5 + vtreat-1.0.1/vtreat/R/utils.R | 4 - vtreat-1.0.1/vtreat/R/vtreatImpl.R | 2 vtreat-1.0.1/vtreat/README.md | 24 ++++---- vtreat-1.0.1/vtreat/build/vignette.rds |binary vtreat-1.0.1/vtreat/inst/doc/SavingTreamentPlans.html | 4 - vtreat-1.0.1/vtreat/inst/doc/vtreat.html | 48 ++++++++-------- vtreat-1.0.1/vtreat/inst/doc/vtreatCrossFrames.html | 52 ++++++++--------- vtreat-1.0.1/vtreat/inst/doc/vtreatGrouping.html | 4 - vtreat-1.0.1/vtreat/inst/doc/vtreatOverfit.html | 36 ++++++------ vtreat-1.0.1/vtreat/inst/doc/vtreatRareLevels.html | 4 - vtreat-1.0.1/vtreat/inst/doc/vtreatScaleMode.html | 4 - vtreat-1.0.1/vtreat/inst/doc/vtreatSignificance.html | 22 +++---- vtreat-1.0.1/vtreat/inst/doc/vtreatSplitting.html | 4 - vtreat-1.0.1/vtreat/inst/doc/vtreatVariableTypes.html | 54 +++++++++--------- 18 files changed, 156 insertions(+), 156 deletions(-)
Title: Time Series Clustering Utilities
Description: A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.
Author: Pablo Montero Manso, José Antonio Vilar
Maintainer: Pablo Montero <pmontm@gmail.com>
Diff between TSclust versions 1.2.3 dated 2014-11-18 and 1.2.4 dated 2017-10-16
ChangeLog | 12 +++ DESCRIPTION | 10 +- MD5 | 12 +-- NAMESPACE | 11 ++ R/diss.R | 240 +++++++++++++++++++++++++++++++++++++----------------------- R/sax.R | 2 man/SAX.Rd | 2 7 files changed, 185 insertions(+), 104 deletions(-)
Title: Collection of Convenient Functions for Common Statistical
Computations
Description: Collection of convenient functions for common statistical computations,
which are not directly provided by R's base or stats packages.
This package aims at providing, first, shortcuts for statistical
measures, which otherwise could only be calculated with additional
effort (like standard errors or root mean squared errors). Second,
these shortcut functions are generic (if appropriate), and can be
applied not only to vectors, but also to other objects as well
(e.g., the Coefficient of Variation can be computed for vectors,
linear models, or linear mixed models; the r2()-function returns
the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects).
The focus of most functions lies on summary statistics or fit
measures for regression models, including generalized linear
models and mixed effects models. However, some of the functions
also deal with other statistical measures, like Cronbach's Alpha,
Cramer's V, Phi etc.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>
Diff between sjstats versions 0.11.2 dated 2017-09-28 and 0.12.0 dated 2017-10-16
sjstats-0.11.2/sjstats/NEWS |only sjstats-0.12.0/sjstats/DESCRIPTION | 16 sjstats-0.12.0/sjstats/MD5 | 46 sjstats-0.12.0/sjstats/NAMESPACE | 14 sjstats-0.12.0/sjstats/NEWS.md | 415 +++--- sjstats-0.12.0/sjstats/R/HDI.R | 15 sjstats-0.12.0/sjstats/R/S3-methods.R | 40 sjstats-0.12.0/sjstats/R/helpfunctions.R | 4 sjstats-0.12.0/sjstats/R/icc.R | 750 ++++++------ sjstats-0.12.0/sjstats/R/merMod_p.R | 240 +-- sjstats-0.12.0/sjstats/R/odds_to_rr.R | 2 sjstats-0.12.0/sjstats/R/pred_vars.R | 163 ++ sjstats-0.12.0/sjstats/R/pseudo_r2.R | 2 sjstats-0.12.0/sjstats/R/se.R | 639 +++++----- sjstats-0.12.0/sjstats/R/tidy_stan.R | 70 - sjstats-0.12.0/sjstats/R/typical.R | 193 +-- sjstats-0.12.0/sjstats/build/partial.rdb |binary sjstats-0.12.0/sjstats/build/vignette.rds |binary sjstats-0.12.0/sjstats/inst/doc/anova-statistics.html | 4 sjstats-0.12.0/sjstats/inst/doc/mixedmodels-statistics.html | 4 sjstats-0.12.0/sjstats/man/hdi.Rd | 3 sjstats-0.12.0/sjstats/man/pred_vars.Rd | 46 sjstats-0.12.0/sjstats/man/reexports.Rd |only sjstats-0.12.0/sjstats/man/tidy_stan.Rd | 3 sjstats-0.12.0/sjstats/man/typical_value.Rd | 36 25 files changed, 1518 insertions(+), 1187 deletions(-)
Title: Analysis of Single-Cell Viral Growth Curves
Description: Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model (sigmoidal, double sigmoidal, no signal or ambiguous) best describes the data. No signal means the intensity does not reach a high enough point or does not change at all over time. Sigmoidal means intensity starts from a small number than climbs to a maximum. Double sigmoidal means intensity starts from a small number, climbs to a maximum then starts to decay. After the decision between those four options, the algorithm gives the sigmoidal (or double sigmoidal) associated parameter values that quantifies the time intensity curve. The origin of the package name came from "SIngle CEll Growth Analysis in R".
Author: M. Umut Caglar [aut, cre],
Claus O. Wilke [aut]
Maintainer: M. Umut Caglar <umut.caglar@gmail.com>
Diff between sicegar versions 0.2 dated 2017-07-11 and 0.2.2 dated 2017-10-16
DESCRIPTION | 12 +-- MD5 | 32 ++++---- R/dataInputCheck.R | 9 +- R/mainFunctions.R | 10 +- R/normalizationFunction.R | 8 +- R/parameterCalculation.R | 3 README.md |only build/vignette.rds |binary inst/doc/additional_parameters.html | 124 ++++++++++++++++---------------- inst/doc/categorizing_fits.Rmd | 6 - inst/doc/categorizing_fits.html | 18 ++-- inst/doc/fitting_individual_models.html | 20 ++--- inst/doc/introduction.html | 24 +++--- inst/doc/plotting_fitted_models.html | 32 ++++---- man/fitAndCategorize.Rd | 8 +- tests |only vignettes/categorizing_fits.Rmd | 6 - 17 files changed, 157 insertions(+), 155 deletions(-)
Title: Fetch 'GeOMe-db' FIMS Data
Description: The Genomic Observatory Metadatabase (GeOMe Database) is an open access repository for
geographic and ecological metadata associated with sequenced samples. This package is used to retrieve
GeOMe data for analysis. See <http://www.geome-db.org> for more information regarding GeOMe.
Author: RJ Ewing
Maintainer: RJ Ewing<ewing.rj@gmail.com>
Diff between geomedb versions 0.1 dated 2017-05-03 and 0.2 dated 2017-10-16
DESCRIPTION | 10 +++++----- MD5 | 6 +++--- R/FimsUtils.R | 3 ++- README.md | 15 +++++++++------ 4 files changed, 19 insertions(+), 15 deletions(-)
Title: Efficient Sampling for Gaussian Linear Regression with Arbitrary
Priors
Description: Efficient sampling for Gaussian linear regression with arbitrary priors.
Author: P. Richard Hahn, Jingyu He and Hedibert Lopes
Maintainer: Jingyu He <jingyu.he@chicagobooth.edu>
Diff between bayeslm versions 0.3.0 dated 2017-09-26 and 0.3.1 dated 2017-10-16
DESCRIPTION | 8 +++---- MD5 | 24 +++++++++++------------ R/RcppExports.R | 20 +++++++++---------- R/bayeslm.default.R | 12 +++++------ R/bayeslm.formula.R | 12 +++++------ man/bayeslm.Rd | 7 +++--- src/RcppExports.cpp | 54 ++++++++++++++++++++++++++++------------------------ src/asymmetric.cpp | 4 +-- src/bayeslm.cpp | 4 +-- src/blasso.cpp | 4 +-- src/horseshoe.cpp | 4 +-- src/nonlocal.cpp | 4 +-- src/ridge.cpp | 4 +-- 13 files changed, 84 insertions(+), 77 deletions(-)
Title: Easily Tidy Data with 'spread()' and 'gather()' Functions
Description: An evolution of 'reshape2'. It's designed specifically for data
tidying (not general reshaping or aggregating) and works well with
'dplyr' data pipelines.
Author: Hadley Wickham [aut, cre],
Lionel Henry [aut],
RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Diff between tidyr versions 0.7.1 dated 2017-09-01 and 0.7.2 dated 2017-10-16
DESCRIPTION | 6 MD5 | 18 - NEWS.md | 8 R/gather.R | 4 R/nest.R | 4 R/spread.R | 4 inst/doc/tidy-data.html | 573 +++++++++++++++++++------------------- src/melt.cpp | 29 + tests/testthat/test-gather.R | 1 tests/testthat/test-underscored.R | 24 + 10 files changed, 359 insertions(+), 312 deletions(-)
Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and
unified Future API for sequential and parallel processing of R
expression via futures. The simplest way to evaluate an expression
in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`.
This package implements sequential, multicore, multisession, and
cluster futures. With these, R expressions can be evaluated on the
local machine, on in parallel a set of local machines, or distributed
on a mix of local and remote machines.
Extensions to this package implements additional backends for
processing futures via compute cluster schedulers etc.
Because of its unified API, there is no need to modify code in order
switch from sequential on the local machine to, say, distributed
processing on a remote compute cluster.
Another strength of this package is that global variables and functions
are automatically identified and exported as needed, making it
straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>
Diff between future versions 1.6.1 dated 2017-09-09 and 1.6.2 dated 2017-10-16
DESCRIPTION | 8 ++--- MD5 | 40 ++++++++++++------------- NAMESPACE | 1 NEWS | 18 +++++++++++ R/ClusterFuture-class.R | 7 +--- R/Future-class.R | 3 + R/backtrace.R | 9 ++++- R/options.R | 2 - R/tweak.R | 31 +++++++++++++------- R/utils.R | 57 +++++++++++++++++++------------------ R/zzz.plan.R | 2 - build/vignette.rds |binary inst/doc/future-1-overview.html | 2 - inst/doc/future-1-overview.md.rsp | 2 - man/future.options.Rd | 2 - man/plan.Rd | 9 +++-- tests/backtrace.R | 27 +++++++++++++++++ tests/objectSize.R | 4 +- tests/plan.R | 4 ++ tests/utils.R | 33 +++++++++++++++++++++ vignettes/future-1-overview.md.rsp | 2 - 21 files changed, 184 insertions(+), 79 deletions(-)
Title: Directional Statistics
Description: A collection of functions for directional data analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000).
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>
Diff between Directional versions 2.8 dated 2017-07-25 and 2.9 dated 2017-10-16
DESCRIPTION | 8 +- MD5 | 162 ++++++++++++++++++++++----------------------- NAMESPACE | 5 - R/Arotation.R | 1 R/ESAGdensity.R | 2 R/circ.cor1.R | 5 - R/circ.summary.R | 2 R/circlin.cor.R | 14 --- R/conc.test.R | 1 R/dirknn.R | 53 ++++++++------ R/dirknn.tune.R | 49 +------------ R/knn.reg.R | 95 ++++++++++++-------------- R/knnreg.tune.R | 34 ++------- R/lr.aov.R | 1 R/lr.circaov.R | 1 R/rbingham.R | 1 R/rmixvmf.R | 1 R/rsop.R | 2 R/spher.cor.R | 1 R/spml.reg.R | 9 -- R/vmf.contour.R | 7 - R/vmf.da.R | 2 R/wood.mle.R | 1 man/Arotation.Rd | 2 man/Directional-package.Rd | 8 +- man/acg.Rd | 2 man/bic.mixvmf.Rd | 2 man/circ.cor1.Rd | 2 man/circ.summary.Rd | 2 man/circlin.cor.Rd | 2 man/conc.test.Rd | 2 man/dirknn.Rd | 28 +++---- man/dirknn.tune.Rd | 2 man/euclid.Rd | 2 man/euclid.inv.Rd | 2 man/f.rbing.Rd | 2 man/fb.saddle.Rd | 2 man/fishkent.Rd | 2 man/group.gof.Rd | 2 man/group.vm.Rd | 2 man/hcf.aov.Rd | 2 man/hcf.circaov.Rd | 2 man/kent.contour.Rd | 2 man/kent.datacontour.Rd | 2 man/kent.logcon.Rd | 2 man/kent.mle.Rd | 2 man/knn.reg.Rd | 14 +-- man/knnreg.tune.Rd | 2 man/kuiper.Rd | 2 man/lambert.Rd | 2 man/lambert.inv.Rd | 2 man/meandir.test.Rd | 2 man/mediandir.Rd | 2 man/mix.vmf.Rd | 2 man/mixvmf.contour.Rd | 2 man/pvm.Rd | 2 man/rayleigh.Rd | 2 man/rbingham.Rd | 2 man/rfb.Rd | 2 man/rkent.Rd | 2 man/rmixvmf.Rd | 2 man/rot.matrix.Rd | 2 man/rotation.Rd | 2 man/rsop.Rd | 2 man/rvmf.Rd | 2 man/rvonmises.Rd | 2 man/spher.cor.Rd | 2 man/spher.reg.Rd | 2 man/spherconc.test.Rd | 2 man/spml.reg.Rd | 2 man/tang.conc.Rd | 2 man/vec.Rd | 2 man/vm.kde.Rd | 2 man/vmf.Rd | 2 man/vmf.contour.Rd | 2 man/vmf.da.Rd | 4 - man/vmf.kde.Rd | 2 man/vmf.kerncontour.Rd | 2 man/vmfda.pred.Rd | 2 man/vmfkde.tune.Rd | 2 man/vmkde.tune.Rd | 2 man/wood.mle.Rd | 2 82 files changed, 275 insertions(+), 346 deletions(-)
Title: Symbolic Differentiation
Description: R-based solution for symbolic differentiation. It admits
user-defined function as well as function substitution
in arguments of functions to be differentiated. Some symbolic
simplification is part of the work.
Author: Andrew Clausen [aut],
Serguei Sokol [aut, cre]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>
Diff between Deriv versions 3.8.1 dated 2017-06-14 and 3.8.2 dated 2017-10-16
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- NEWS | 6 ++++++ R/Deriv.R | 6 +++--- man/Deriv-package.Rd | 4 ++-- tests/testthat/test_Deriv.R | 9 +++++++++ 6 files changed, 29 insertions(+), 14 deletions(-)
Title: Visualization of a Correlation Matrix
Description: A graphical display of a correlation matrix or general matrix.
It also contains some algorithms to do matrix reordering. In addition,
corrplot is good at details, including choosing color, text labels,
color labels, layout, etc.
Author: Taiyun Wei [cre, aut],
Viliam Simko [aut],
Michael Levy [ctb],
Yihui Xie [ctb],
Yan Jin [ctb],
Jeff Zemla [ctb]
Maintainer: Taiyun Wei <weitaiyun@gmail.com>
Diff between corrplot versions 0.77 dated 2016-04-21 and 0.84 dated 2017-10-16
corrplot-0.77/corrplot/NEWS |only corrplot-0.77/corrplot/README.md |only corrplot-0.84/corrplot/DESCRIPTION | 30 corrplot-0.84/corrplot/MD5 | 66 corrplot-0.84/corrplot/NAMESPACE | 23 corrplot-0.84/corrplot/R/colorlegend.R | 189 - corrplot-0.84/corrplot/R/cor-mtest.R |only corrplot-0.84/corrplot/R/corrMatOrder.R | 158 - corrplot-0.84/corrplot/R/corrRect.R | 49 corrplot-0.84/corrplot/R/corrRect.hclust.R | 83 corrplot-0.84/corrplot/R/corrplot-package.R |only corrplot-0.84/corrplot/R/corrplot.R | 1813 +++++++------ corrplot-0.84/corrplot/R/corrplot.mixed.R | 142 - corrplot-0.84/corrplot/build/vignette.rds |binary corrplot-0.84/corrplot/inst/CITATION |only corrplot-0.84/corrplot/inst/NEWS |only corrplot-0.84/corrplot/inst/doc/corrplot-intro.R | 320 +- corrplot-0.84/corrplot/inst/doc/corrplot-intro.Rmd | 550 ++- corrplot-0.84/corrplot/inst/doc/corrplot-intro.html | 912 +++--- corrplot-0.84/corrplot/man/colorlegend.Rd | 142 - corrplot-0.84/corrplot/man/cor.mtest.Rd |only corrplot-0.84/corrplot/man/corrMatOrder.Rd | 155 - corrplot-0.84/corrplot/man/corrRect.Rd | 121 corrplot-0.84/corrplot/man/corrRect.hclust.Rd | 137 corrplot-0.84/corrplot/man/corrplot-package.Rd | 72 corrplot-0.84/corrplot/man/corrplot.Rd | 911 +++--- corrplot-0.84/corrplot/man/corrplot.mixed.Rd | 124 corrplot-0.84/corrplot/tests/testthat.R | 8 corrplot-0.84/corrplot/tests/testthat/test-colorlegend.R | 74 corrplot-0.84/corrplot/tests/testthat/test-cor-mtest.R |only corrplot-0.84/corrplot/tests/testthat/test-corrplot.R | 369 +- corrplot-0.84/corrplot/vignettes/corrplot-intro.Rmd | 550 ++- corrplot-0.84/corrplot/vignettes/example-colorlegend.R | 48 corrplot-0.84/corrplot/vignettes/example-corrMatOrder.R | 56 corrplot-0.84/corrplot/vignettes/example-corrRect.R | 62 corrplot-0.84/corrplot/vignettes/example-corrRect.hclust.R | 62 corrplot-0.84/corrplot/vignettes/example-corrplot.R | 387 +- corrplot-0.84/corrplot/vignettes/example-corrplot.mixed.R | 26 38 files changed, 4303 insertions(+), 3336 deletions(-)
Title: Bayesian Structure Learning in Graphical Models using
Birth-Death MCMC
Description: Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889> and Mohammadi et al. (2017) <doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Author: Abdolreza Mohammadi and Ernst Wit
Maintainer: Abdolreza Mohammadi <a.mohammadi@rug.nl>
Diff between BDgraph versions 2.40 dated 2017-08-14 and 2.41 dated 2017-10-16
DESCRIPTION | 8 MD5 | 68 +- NEWS | 8 R/bdgraph.R | 10 R/bdgraph.mpl.R | 38 - R/bdgraph.sim.R | 17 R/check.os.R |only R/compare.R | 14 R/gnorm.R | 14 R/hill_climb_algorithm.R | 141 ++++- R/hill_climb_binary.R |only R/plotroc.R | 16 R/test.R |only man/BDgraph-internal.Rd | 7 man/bdgraph.Rd | 2 man/bdgraph.mpl.Rd | 5 src/BDgraph-win.def |only src/Makevars | 4 src/MyLapack.h | 9 src/bd_for_ts.cpp | 13 src/check_nthread.cpp |only src/check_os.cpp |only src/copula.cpp | 14 src/copula.h | 10 src/gcgm_DMH.cpp | 15 src/gcgm_bd.cpp | 20 src/ggm_DMH.cpp | 23 src/ggm_bd.cpp | 25 - src/ggm_mpl_bd.cpp | 163 +++--- src/gm_mpl_Hill_Climb.cpp | 390 +++++++++------- src/gm_mpl_bd_dis.cpp | 1095 ++++++++++++++++++++++++++++++---------------- src/gm_rj.cpp | 13 src/init.c | 8 src/matrix.cpp | 43 + src/matrix.h | 11 src/rgwish.cpp | 8 src/rgwish.h | 11 src/test_c.cpp |only src/util.h |only 39 files changed, 1333 insertions(+), 890 deletions(-)
Title: Perform Spatial Error Estimation and Variable Importance in
Parallel
Description: Implements spatial error estimation and
permutation-based variable importance measures for predictive models using
spatial cross-validation and spatial block bootstrap.
Author: Alexander Brenning [aut, cre],
Patrick Schratz [aut],
Tobias Herrmann [aut]
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>
Diff between sperrorest versions 2.1.0 dated 2017-09-26 and 2.1.1 dated 2017-10-16
DESCRIPTION | 8 - MD5 | 38 +++---- NEWS | 7 + NEWS.md | 6 + R/helper_funs.R | 3 R/processing.R | 52 +++++++--- R/resample.R | 16 ++- R/sperrorest.R | 92 +++++++++++++----- R/sperrorest_error.R | 18 ++- R/sperrorest_misc.R | 23 +++- R/sperrorest_resampling.R | 50 +++++----- R/summary_functions.R | 14 ++ build/vignette.rds |binary man/err_default.Rd | 4 man/runreps.Rd | 13 +- tests/testthat/test-processing.R | 17 +-- tests/testthat/test-resample.R | 7 - tests/testthat/test-sperrorest-resampling.R | 12 +- tests/testthat/test-sperrorest-summary.R | 4 tests/testthat/test-sperrorest.R | 140 ++++++++++++++++++++-------- 20 files changed, 352 insertions(+), 172 deletions(-)
Title: Heatmaps for Multiple Network Data
Description: Simplify the exploratory data analysis process for multiple network data sets with the help
of hierarchical clustering and heatmaps. Multiple network data consists of multiple disjoint
networks that share common graph, node and edge variables. Contains the tools necessary to
convert this raw data into a single dynamic report, summarizing the relationships
of the graph, node and structural characteristics of the networks.
Author: Phil Boileau [aut, cre]
Maintainer: Phil Boileau <philippe.boileau@mail.concordia.ca>
Diff between neatmaps versions 1.0.5 dated 2017-08-28 and 1.0.6 dated 2017-10-16
DESCRIPTION | 13 +++++---- MD5 | 6 ++-- README.md | 66 ++++++++++++++++++++++++++++++++++++++++++++++++-- inst/rmd/template.Rmd | 17 ++++++------ 4 files changed, 82 insertions(+), 20 deletions(-)
Title: Generalized Synthetic Control Method
Description: Provides causal inference with interactive fixed-effect models. It imputes counterfactuals for each treated unit using control group information based on a linear interactive fixed effects model that incorporates unit-specific intercepts interacted with time-varying coefficients. This method generalizes the synthetic control method to the case of multiple treated units and variable treatment periods, and improves efficiency and interpretability. This version supports unbalanced panels. Reference: Yiqing Xu (2017) <doi:10.1017/pan.2016.2>.
Author: Yiqing Xu, Licheng Liu
Maintainer: Yiqing Xu <yiqingxu@ucsd.edu>
Diff between gsynth versions 1.0.5 dated 2017-10-12 and 1.0.6 dated 2017-10-16
DESCRIPTION | 14 +++++++------ MD5 | 23 +++++++++++----------- R/gsynth.R | 51 +++++++++++++++++++++++++++++++------------------- README.md |only man/gsynth-package.Rd | 4 --- man/gsynth.Rd | 7 ++---- man/plot.gsynth.Rd | 4 +-- man/print.gsynth.Rd | 4 +-- man/simdata.Rd | 4 +-- man/turnout.Rd | 6 ++--- src/Makevars | 2 - src/Makevars.win | 2 - src/interFE.cpp | 42 +++++++++++++++++++++++++++-------------- 13 files changed, 95 insertions(+), 68 deletions(-)
Title: Fishery Science Methods and Models in R
Description: Fishery science methods and models from published literature and contributions from colleagues.
Author: Gary A. Nelson <gary.nelson@state.ma.us>
Maintainer: Gary A. Nelson <gary.nelson@state.ma.us>
Diff between fishmethods versions 1.10-3 dated 2017-07-13 and 1.10-4 dated 2017-10-16
DESCRIPTION | 9 +-- MD5 | 30 +++++++--- NAMESPACE | 9 +-- R/catchmsy.R | 8 +- R/dbsra.R | 135 +++++++++++++++++++++++++++++++++++++----------- R/dlproj.R | 25 ++------ R/grotagplus.R |only R/growth.R | 8 +- R/plot.grotagplus.R |only R/print.grotagplus.R |only R/vblrt.R | 4 - data/P.donacina.rda |only data/rig.rda |only man/P.donacina.Rd |only man/dbsra.Rd | 22 ++++++- man/dlproj.Rd | 2 man/grotagplus.Rd |only man/growth.Rd | 5 + man/plot.grotagplus.Rd |only man/print.grotagplus.Rd |only man/rig.Rd |only 21 files changed, 177 insertions(+), 80 deletions(-)
Title: Estimate Univariate Gaussian or Student's t Mixture
Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR) and
Student's t Mixture Autoregressive (StMAR) models, quantile residual tests, graphical diagnostics,
forecast and simulate from GMAR and StMAR processes. Also general linear constraints and restricting
autoregressive parameters to be the same for all regimes are supported.
Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>,
Leena Kalliovirta (2012) <doi:10.1111/j.1368-423X.2011.00364.x>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>
Diff between uGMAR versions 1.0.1 dated 2017-08-29 and 1.0.2 dated 2017-10-16
DESCRIPTION | 6 MD5 | 86 ++--- NAMESPACE | 32 - R/MAINest.R | 6 R/geneticAlgorithm.R | 8 R/loglikelihood.R | 2 R/quantileResiduals.R | 449 +++++++++++++------------- README.md | 46 +- build/vignette.rds |binary inst/doc/intro-to-uGMAR.Rmd | 236 +++++++------- inst/doc/intro-to-uGMAR.html | 288 ++++++++--------- man/GAfit.Rd | 284 ++++++++-------- man/VIX.Rd | 36 +- man/changeRegime.Rd | 184 +++++----- man/checkAndCorrectData.Rd | 40 +- man/checkConstraintMat.Rd | 68 ++-- man/checkPM.Rd | 38 +- man/extractRegime.Rd | 178 +++++----- man/fitGMAR.Rd | 470 ++++++++++++++-------------- man/forecastGMAR.Rd | 265 ++++++++------- man/getOmega.Rd | 174 +++++----- man/isStationary.Rd | 220 ++++++------- man/isStationary_int.Rd | 136 ++++---- man/loglikelihood.Rd | 223 +++++++------ man/loglikelihood_int.Rd | 224 ++++++------- man/mixingWeights.Rd | 228 ++++++------- man/mixingWeights_int.Rd | 182 +++++----- man/nParams.Rd | 76 ++-- man/parameterChecks.Rd | 84 ++--- man/plotGMAR.Rd | 270 ++++++++-------- man/quantileResidualTests.Rd | 312 +++++++++--------- man/quantileResiduals.Rd | 242 +++++++------- man/quantileResiduals_int.Rd | 190 +++++------ man/randomIndividual.Rd | 360 ++++++++++----------- man/randomIndividual_int.Rd | 244 +++++++------- man/reformConstrainedPars.Rd | 140 ++++---- man/reformParameters.Rd | 136 ++++---- man/simulateGMAR.Rd | 229 +++++++------ man/sortComponents.Rd | 164 ++++----- man/standardErrors.Rd | 162 ++++----- tests/testthat/test_getOmega.R | 236 +++++++------- tests/testthat/test_quantileResidualTests.R | 142 ++++---- tests/testthat/test_quantileResiduals.R | 102 +++--- vignettes/intro-to-uGMAR.Rmd | 236 +++++++------- 44 files changed, 3737 insertions(+), 3697 deletions(-)
Title: Regularization for Variable Selection in Model-Based Clustering
and Discriminant Analysis
Description: Performs a regularization approach to variable selection in the
model-based clustering and classification frameworks.
First, the variables are arranged in order with a lasso-like procedure.
Second, the method of Maugis, Celeux, and Martin-Magniette (2009, 2011)
<doi:10.1016/j.csda.2009.04.013>, <doi:10.1016/j.jmva.2011.05.004>
is adapted to define the role of variables in the two frameworks.
Author: Mohammed Sedki, Gilles Celeux, Cathy Maugis-Rabusseau
Maintainer: Mohammed Sedki <mohammed.sedki@u-psud.fr>
Diff between SelvarMix versions 1.2 dated 2016-11-07 and 1.2.1 dated 2017-10-16
DESCRIPTION | 8 - MD5 | 16 +- R/ClusteringEMGlasso.R | 237 +++++++++++++++++----------------- R/DiscriminantAnalysisGlasso.R | 101 +++++++------- R/RcppExports.R | 12 - R/SelvarClustLasso.R | 279 ++++++++++++++++++++--------------------- R/VariableSelection.R | 247 ++++++++++++++++++------------------ data/wine.rda |binary src/RcppExports.cpp | 27 +++ 9 files changed, 471 insertions(+), 456 deletions(-)
Title: Multivariate Data Analysis Laboratory
Description: An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools, and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users). Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.
Author: Nelson Lee Afanador, Thanh Tran, Lionel Blanchet, and Richard Baumgartner
Maintainer: Nelson Lee Afanador <nelson.afanador@mvdalab.com>
Diff between mvdalab versions 1.3 dated 2017-10-04 and 1.4 dated 2017-10-16
DESCRIPTION | 8 ++++---- MD5 | 8 +++++++- R/MultCapability.R |only data/Wang_Chen.rda |only data/Wang_Chen_Sim.rda |only man/MultCapability.Rd |only man/Wang_Chen.Rd |only man/Wang_Chen_Sim.Rd |only 8 files changed, 11 insertions(+), 5 deletions(-)
Title: Quickly View Data Frames in 'Excel', Build Folder Paths and
Create Date Vectors
Description: Contains several useful navigation helper functions, including easily building
folder paths, quick viewing dataframes in 'Excel', creating date vectors and changing the
console prompt to reflect time.
Author: Nico Katzke [aut, cre]
Maintainer: Nico Katzke <nfkatzke@gmail.com>
Diff between rmsfuns versions 0.0.0.1 dated 2017-10-14 and 0.0.0.2 dated 2017-10-16
DESCRIPTION | 10 +++++----- MD5 | 8 ++++---- R/dateconverter.R | 2 +- inst/doc/rmsfuns.html | 4 ++-- man/dateconverter.Rd | 2 +- 5 files changed, 13 insertions(+), 13 deletions(-)
Title: Seasonal/Sequential (Instants/Durations, Even or not) Time
Series
Description: Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : 'POSIXcti', 'POSIXctp', 'TimeIntervalDataFrame', 'TimeInstantDataFrame', 'SubtimeDataFrame' ; methods to switch from a class to another and to modify the time support of series (hourly time series to daily time series for instance) are also defined. Tools provided can be used for instance to handle environmental monitoring data (not always produced on a regular time base).
Author: Vladislav Navel
Maintainer: Vladislav Navel <vnavel@yahoo.fr>
Diff between timetools versions 1.12.2 dated 2017-09-15 and 1.12.3 dated 2017-10-16
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++------- R/TimeInstantDataFrame.R | 7 +++++-- R/TimeIntervalDataFrame.R | 11 +++++++++-- README | 4 ++++ man/TimeInstantDataFrame-class.Rd | 4 ++-- man/TimeIntervalDataFrame-class.Rd | 4 ++-- man/timetools-package.Rd | 4 ++-- 8 files changed, 35 insertions(+), 21 deletions(-)
Title: Data Exchange Between R and LabKey Server
Description: The LabKey client library for R makes it easy for R users to
load live data from a LabKey Server, <http://www.labkey.com/>,
into the R environment for analysis, provided users have permissions
to read the data. It also enables R users to insert, update, and
delete records stored on a LabKey Server, provided they have appropriate
permissions to do so.
Author: Peter Hussey
Maintainer: Cory Nathe <cnathe@labkey.com>
Diff between Rlabkey versions 2.1.135 dated 2017-06-19 and 2.1.136 dated 2017-10-16
DESCRIPTION | 10 +-- MD5 | 112 ++++++++++++++++++------------------ NEWS | 5 + R/RcppExports.R | 15 ++++ R/fromJSON2.R | 2 R/ifcookie.R | 2 R/labkey.curlOptions.R | 2 R/labkey.defaults.R | 2 R/labkey.deleteRows.R | 2 R/labkey.executeSql.R | 8 -- R/labkey.getFolders.R | 2 R/labkey.getQueryInfo.R | 2 R/labkey.getQueryLists.R | 2 R/labkey.getSchemas.R | 2 R/labkey.importRows.R | 2 R/labkey.insertRows.R | 2 R/labkey.makeRemotePath.R | 2 R/labkey.saveBatch.R | 2 R/labkey.selectRows.R | 76 ++++++++++++++++-------- R/labkey.setCurlOptions.R | 2 R/labkey.updateRows.R | 2 R/makeDF.R | 14 ++-- R/makeFilter.R | 2 R/parseHeader.R | 30 ++++----- R/schemaObjects.R | 4 - build/vignette.rds |binary inst/doc/RlabkeyExample.pdf |binary man/Rlabkey-package.Rd | 4 - man/RlabkeyUsersGuide.Rd | 5 - man/getFolderPath.Rd | 8 -- man/getLookups.Rd | 4 - man/getRows.Rd | 4 - man/getSchema.Rd | 4 - man/getSession.Rd | 37 ----------- man/labkey.deleteRows.Rd | 3 man/labkey.executeSql.Rd | 2 man/labkey.getDefaultViewDetails.Rd | 2 man/labkey.getFolders.Rd | 6 - man/labkey.getLookupDetails.Rd | 2 man/labkey.getQueries.Rd | 10 +-- man/labkey.getQueryDetails.Rd | 2 man/labkey.getQueryViews.Rd | 2 man/labkey.getSchemas.Rd | 3 man/labkey.importRows.Rd | 3 man/labkey.insertRows.Rd | 3 man/labkey.makeRemotePath.Rd | 16 ++--- man/labkey.saveBatch.Rd | 3 man/labkey.selectRows.Rd | 14 ++-- man/labkey.setDefaults.Rd | 5 - man/labkey.updateRows.Rd | 2 man/lsFolders.Rd | 11 --- man/lsProjects.Rd | 5 + man/lsSchemas.Rd | 2 man/makeFilter.Rd | 35 ----------- man/saveResults.Rd | 4 - src/RJSON_parser.c | 2 src/RJSON_parser.h | 2 57 files changed, 243 insertions(+), 268 deletions(-)
Title: Hierarchical Ensemble Methods for Directed Acyclic Graphs
Description: An implementation of Hierarchical Ensemble Methods for Directed Acyclic Graphs (DAGs). The 'HEMDAG' package can be used to enhance the predictions of virtually any flat learning method, by taking into account the hierarchical nature of the classes of a bio-ontology. 'HEMDAG' is specifically designed for exploiting the hierarchical relationships of DAG-structured taxonomies, such as the Human Phenotype Ontology (HPO) or the Gene Ontology (GO), but it can be also safely applied to tree-structured taxonomies (as FunCat), since trees are DAGs. 'HEMDAG' scale nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples. (Marco Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini (2017) <doi:10.1186/s12859-017-1854-y>).
Author: Marco Notaro [aut, cre] and Giorgio Valentini [aut]
(AnacletoLab, Dipartimento di Informatica, Universita' degli Studi di Milano)
Maintainer: Marco Notaro <marco.notaro@unimi.it>
Diff between HEMDAG versions 1.0.0 dated 2017-08-11 and 1.1.1 dated 2017-10-16
HEMDAG-1.0.0/HEMDAG/R/HEMDAG.1.0.0.R |only HEMDAG-1.0.0/HEMDAG/man/htd.Rd |only HEMDAG-1.1.1/HEMDAG/CHANGELOG |only HEMDAG-1.1.1/HEMDAG/DESCRIPTION | 14 - HEMDAG-1.1.1/HEMDAG/MD5 | 118 ++++++----- HEMDAG-1.1.1/HEMDAG/NAMESPACE | 21 + HEMDAG-1.1.1/HEMDAG/R/IO.fun.R |only HEMDAG-1.1.1/HEMDAG/R/descens.R |only HEMDAG-1.1.1/HEMDAG/R/graph.utility.R |only HEMDAG-1.1.1/HEMDAG/R/heuristic.methods.R |only HEMDAG-1.1.1/HEMDAG/R/htd.R |only HEMDAG-1.1.1/HEMDAG/R/norm.fun.R |only HEMDAG-1.1.1/HEMDAG/R/perf.meas.R |only HEMDAG-1.1.1/HEMDAG/R/pkg.attach.R |only HEMDAG-1.1.1/HEMDAG/R/pkg.import.R |only HEMDAG-1.1.1/HEMDAG/R/tpr.R |only HEMDAG-1.1.1/HEMDAG/inst/CITATION |only HEMDAG-1.1.1/HEMDAG/inst/doc/HEMDAG.pdf |binary HEMDAG-1.1.1/HEMDAG/man/AUPRC.single.class.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/AUPRC.single.over.classes.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/AUROC.single.class.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/AUROC.single.over.classes.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/DESCENS.CV.Rd |only HEMDAG-1.1.1/HEMDAG/man/DESCENS.HOLDOUT.Rd |only HEMDAG-1.1.1/HEMDAG/man/DESCENS.Rd |only HEMDAG-1.1.1/HEMDAG/man/Do.FLAT.scores.normalization.Rd | 4 HEMDAG-1.1.1/HEMDAG/man/Do.HTD.Rd | 31 +- HEMDAG-1.1.1/HEMDAG/man/Do.HTD.holdout.Rd | 37 +-- HEMDAG-1.1.1/HEMDAG/man/Do.descens.threshold.free.Rd |only HEMDAG-1.1.1/HEMDAG/man/Do.descens.threshold.free.holdout.Rd |only HEMDAG-1.1.1/HEMDAG/man/Do.full.annotation.matrix.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/Do.heuristic.methods.Rd |only HEMDAG-1.1.1/HEMDAG/man/Do.heuristic.methods.holdout.Rd |only HEMDAG-1.1.1/HEMDAG/man/Do.tpr.threshold.free.Rd | 31 +- HEMDAG-1.1.1/HEMDAG/man/Do.tpr.threshold.free.holdout.Rd | 34 +-- HEMDAG-1.1.1/HEMDAG/man/HEMDAG-package.Rd | 25 +- HEMDAG-1.1.1/HEMDAG/man/HTD-DAG.Rd |only HEMDAG-1.1.1/HEMDAG/man/Heuristic-Methods.Rd |only HEMDAG-1.1.1/HEMDAG/man/Multilabel.F.measure.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/TPR-DAG.Rd | 18 + HEMDAG-1.1.1/HEMDAG/man/TPR.DAG.CV.Rd | 42 ++- HEMDAG-1.1.1/HEMDAG/man/TPR.DAG.HOLDOUT.Rd | 40 ++- HEMDAG-1.1.1/HEMDAG/man/ancestors.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/check.DAG.integrity.Rd | 4 HEMDAG-1.1.1/HEMDAG/man/check.annotation.matrix.integrity.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/children.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/compute.flipped.graph.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/constraints.matrix.Rd | 8 HEMDAG-1.1.1/HEMDAG/man/descendants.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/distances.from.leaves.Rd | 6 HEMDAG-1.1.1/HEMDAG/man/do.edges.from.HPO.obo.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/do.subgraph.Rd | 4 HEMDAG-1.1.1/HEMDAG/man/do.submatrix.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/do.unstratified.cv.data.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/example.datasets.Rd | 23 +- HEMDAG-1.1.1/HEMDAG/man/find.best.f.Rd | 3 HEMDAG-1.1.1/HEMDAG/man/find.leaves.Rd | 4 HEMDAG-1.1.1/HEMDAG/man/full.annotation.matrix.Rd | 6 HEMDAG-1.1.1/HEMDAG/man/graph.levels.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/hierarchical.checkers.Rd | 8 HEMDAG-1.1.1/HEMDAG/man/normalize.max.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/parents.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/read.graph.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/read.undirected.graph.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/root.node.Rd | 4 HEMDAG-1.1.1/HEMDAG/man/specific.annotation.list.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/specific.annotation.matrix.Rd | 12 - HEMDAG-1.1.1/HEMDAG/man/stratified.cross.validation.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/transitive.closure.annotations.Rd | 2 HEMDAG-1.1.1/HEMDAG/man/tupla.matrix.Rd |only HEMDAG-1.1.1/HEMDAG/man/weighted.adjacency.matrix.Rd | 6 HEMDAG-1.1.1/HEMDAG/man/write.graph.Rd | 2 72 files changed, 310 insertions(+), 239 deletions(-)
Title: Design-Based Global and Small-Area Estimations for Multiphase
Forest Inventories
Description: Extensive global and small-area estimation procedures for multiphase
forest inventories under the design-based Monte-Carlo approach are provided.
The implementation includes estimators for simple and cluster sampling
published by Daniel Mandallaz in 2007 (<DOI:10.1201/9781584889779>),
2013 (<DOI:10.1139/cjfr-2012-0381>, <DOI:10.1139/cjfr-2013-0181>,
<DOI:10.1139/cjfr-2013-0449>, <DOI:10.3929/ethz-a-009990020>)
and 2016 (<DOI:10.3929/ethz-a-010579388>). It provides point estimates,
their external- and design-based variances as well as confidence intervals.
The procedures have also been optimized for the use of remote sensing data
as auxiliary information.
Author: Andreas Hill [aut, cre],
Alexander Massey [aut],
Daniel Mandallaz [ctb]
Maintainer: Andreas Hill <andreas.hill@usys.ethz.ch>
Diff between forestinventory versions 0.3.0 dated 2017-10-03 and 0.3.1 dated 2017-10-16
DESCRIPTION | 10 ++++++---- MD5 | 12 ++++++++---- NEWS | 2 ++ R/small_area_nonexhaustive3p.R | 7 ++++--- R/small_area_nonexhaustive3p_cluster.R | 4 ++-- build |only inst/doc |only vignettes |only 8 files changed, 22 insertions(+), 13 deletions(-)
More information about forestinventory at CRAN
Permanent link
Title: Simulation and Prediction with Seasonal ARIMA Models
Description: Functions, classes and methods for time series modelling with ARIMA
and related models. The aim of the package is to provide consistent
interface for the user. For example, a single function
autocorrelations() computes various kinds of
theoretical and sample autocorrelations. This is work in progress,
see the documentation and vignettes for the current functionality.
Author: Georgi N. Boshnakov
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>
Diff between sarima versions 0.4-5 dated 2017-05-22 and 0.5-2 dated 2017-10-16
sarima-0.4-5/sarima/man/sigmaSq-methods.Rd |only sarima-0.5-2/sarima/DESCRIPTION | 18 sarima-0.5-2/sarima/MD5 | 102 - sarima-0.5-2/sarima/NAMESPACE | 23 sarima-0.5-2/sarima/NEWS | 44 sarima-0.5-2/sarima/R/armacalc.R | 11 sarima-0.5-2/sarima/R/autocovariances.R | 196 +- sarima-0.5-2/sarima/R/filterClasses.R | 1111 ++++++------- sarima-0.5-2/sarima/R/modelClasses.R | 1064 +++++++----- sarima-0.5-2/sarima/R/sarima.R | 280 --- sarima-0.5-2/sarima/R/utils.R | 17 sarima-0.5-2/sarima/build/partial.rdb |binary sarima-0.5-2/sarima/build/vignette.rds |binary sarima-0.5-2/sarima/inst/REFERENCES.bib |only sarima-0.5-2/sarima/inst/auto |only sarima-0.5-2/sarima/inst/doc/garch_tests_example.pdf |binary sarima-0.5-2/sarima/inst/doc/white_noise_tests.pdf |binary sarima-0.5-2/sarima/man/ArmaModel-class.Rd | 25 sarima-0.5-2/sarima/man/InterceptSpec-class.Rd |only sarima-0.5-2/sarima/man/SarimaModel-class.Rd | 185 +- sarima-0.5-2/sarima/man/VirtualMonicFilter-class.Rd | 16 sarima-0.5-2/sarima/man/acfGarchTest.Rd |only sarima-0.5-2/sarima/man/acfIidTest.Rd | 54 sarima-0.5-2/sarima/man/acfMaTest.Rd |only sarima-0.5-2/sarima/man/arCoef.Rd |only sarima-0.5-2/sarima/man/armaccf_xe.Rd | 70 sarima-0.5-2/sarima/man/autocorrelations-methods.Rd | 7 sarima-0.5-2/sarima/man/autocorrelations.Rd | 2 sarima-0.5-2/sarima/man/autocovariances-methods.Rd | 2 sarima-0.5-2/sarima/man/coerce-methods.Rd |only sarima-0.5-2/sarima/man/filterCoef-methods.Rd | 16 sarima-0.5-2/sarima/man/filterCoef.Rd | 67 sarima-0.5-2/sarima/man/filterOrder-methods.Rd | 14 sarima-0.5-2/sarima/man/filterPoly-methods.Rd | 13 sarima-0.5-2/sarima/man/filterPolyCoef-methods.Rd | 2 sarima-0.5-2/sarima/man/fun.forecast.Rd | 79 sarima-0.5-2/sarima/man/isStationaryModel.Rd |only sarima-0.5-2/sarima/man/modelCenter.Rd |only sarima-0.5-2/sarima/man/modelCoef-methods.Rd | 53 sarima-0.5-2/sarima/man/modelCoef.Rd | 54 sarima-0.5-2/sarima/man/modelIntercept.Rd |only sarima-0.5-2/sarima/man/modelOrder-methods.Rd | 11 sarima-0.5-2/sarima/man/modelOrder.Rd | 7 sarima-0.5-2/sarima/man/modelPoly-methods.Rd | 8 sarima-0.5-2/sarima/man/modelPolyCoef-methods.Rd | 9 sarima-0.5-2/sarima/man/nSeasons.Rd |only sarima-0.5-2/sarima/man/nUnitRoots.Rd |only sarima-0.5-2/sarima/man/nvcovOfAcf.Rd |only sarima-0.5-2/sarima/man/partialAutocorrelations-methods.Rd | 1 sarima-0.5-2/sarima/man/plot-methods.Rd | 2 sarima-0.5-2/sarima/man/prepareSimSarima.Rd | 42 sarima-0.5-2/sarima/man/rgarch1p1.Rd | 4 sarima-0.5-2/sarima/man/sarima-package.Rd | 24 sarima-0.5-2/sarima/man/sigmaSq.Rd |only sarima-0.5-2/sarima/man/sim_sarima.Rd | 71 sarima-0.5-2/sarima/man/summary.SarimaModel.Rd | 4 sarima-0.5-2/sarima/man/whiteNoiseTest.Rd | 43 sarima-0.5-2/sarima/man/xarmaFilter.Rd | 63 sarima-0.5-2/sarima/tests |only 59 files changed, 2201 insertions(+), 1613 deletions(-)
More information about metaheuristicOpt at CRAN
Permanent link
Title: Latent Markov Models with and without Covariates
Description: Fit certain versions of the Latent Markov model for longitudinal categorical data.
Author: Francesco Bartolucci, Silvia Pandolfi - University of Perugia (IT)
Maintainer: Francesco Bartolucci <bart@stat.unipg.it>
Diff between LMest versions 2.4 dated 2017-06-06 and 2.4.1 dated 2017-10-16
DESCRIPTION | 8 ++++---- MD5 | 5 +++-- inst |only man/LMest-package.Rd | 11 +++++++---- 4 files changed, 14 insertions(+), 10 deletions(-)
Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM
or Gibbs sampling, with optional sampling techniques and kernel term.
Author: Alencar Xavier, William Muir, Shizhong Xu, Katy Rainey.
Maintainer: Alencar Xavier <alenxav@gmail.com>
Diff between bWGR versions 1.4 dated 2017-03-22 and 1.5 dated 2017-10-16
bWGR-1.4/bWGR/R/wgr.R |only bWGR-1.4/bWGR/src/Functions.cpp |only bWGR-1.5/bWGR/DESCRIPTION | 10 +-- bWGR-1.5/bWGR/MD5 | 16 +++--- bWGR-1.5/bWGR/R/RcppExports.R | 82 ++++++++++++++++---------------- bWGR-1.5/bWGR/R/mkr.R | 2 bWGR-1.5/bWGR/R/wgr101517.R |only bWGR-1.5/bWGR/man/bWGR.Rd | 12 +++- bWGR-1.5/bWGR/man/wgr.Rd | 26 +++++----- bWGR-1.5/bWGR/src/RcppExports.cpp | 97 ++++++++++++++++++++++---------------- bWGR-1.5/bWGR/src/wgr101517.cpp |only 11 files changed, 137 insertions(+), 108 deletions(-)
Title: Variable Selection for Model-Based Clustering of Continuous,
Count, Categorical or Mixed-Type Data Set with Missing Values
Description: Variable Selection for model-based clustering managed by the Latent
Class Model. This model analyses mixed-type data (data with continuous and/
or count and/or categorical variables) with missing values (missing at random)
by assuming independence between classes. The one-dimensional marginals of
the components follow standard distributions for facilitating both the model
interpretation and the model selection. The variable selection is led by an
alternated optimization procedure for maximizing the Maximum Integrated
Complete-data Likelihood criterion. The maximum likelihood inference is done
by an EM algorithm for the selected model. This package also performs the
imputation of missing values by taking the expectation of the missing values
conditionally on the model, its parameters and on the observed variables.
Author: Matthieu Marbac and Mohammed Sedki
Maintainer: Mohammed Sedki <mohammed.sedki@u-psud.fr>
Diff between VarSelLCM versions 2.0 dated 2017-09-22 and 2.0.1 dated 2017-10-16
VarSelLCM-2.0.1/VarSelLCM/DESCRIPTION | 8 +++--- VarSelLCM-2.0.1/VarSelLCM/MD5 | 9 +++---- VarSelLCM-2.0.1/VarSelLCM/NAMESPACE | 14 ++++++++--- VarSelLCM-2.0.1/VarSelLCM/man/VarSelCluster.Rd | 30 ++++++++++++++++++++++--- VarSelLCM-2.0.1/VarSelLCM/src/RcppExports.cpp | 12 ++++++++++ VarSelLCM-2.0/VarSelLCM/src/VarSelLCM-init.c |only 6 files changed, 57 insertions(+), 16 deletions(-)
Title: Global Summary Daily Weather Data in R
Description: Provides automated downloading, parsing, cleaning, unit conversion
and formatting of Global Surface Summary of the Day (GSOD) weather data from
the from the USA National Centers for Environmental Information (NCEI) for
use in R. Units are converted from from United States Customary System
(USCS) units to International System of Units (SI). Stations may be
individually checked for number of missing days defined by the user, where
stations with too many missing observations are omitted. Only stations with
valid reported latitude and longitude values are permitted in the final
data. Additional useful elements, saturation vapour pressure (es), actual
vapour pressure (ea) and relative humidity are calculated from the original
data and included in the final data set. The resulting data include station
identification information, state, country, latitude, longitude, elevation,
weather observations and associated flags. Data may be automatically saved
to disk. File output may be returned as a comma-separated values (CSV) or
GeoPackage (GPKG) file. Additional data are included with this R package: a
list of elevation values for stations between -60 and 60 degrees latitude
derived from the Shuttle Radar Topography Measuring Mission (SRTM). For
information on the GSOD data from NCEI, please see the GSOD readme.txt file
available from, <http://www1.ncdc.noaa.gov/pub/data/gsod/readme.txt>.
Author: Adam Sparks [aut, cre] (http://orcid.org/0000-0002-0061-8359),
Tomislav Hengl [aut] (http://orcid.org/0000-0002-9921-5129),
Andrew Nelson [aut] (http://orcid.org/0000-0002-7249-3778)
Maintainer: Adam Sparks <adamhsparks@gmail.com>
Diff between GSODR versions 1.0.6 dated 2017-09-19 and 1.0.7 dated 2017-10-16
GSODR-1.0.6/GSODR/R/GSODR.R |only GSODR-1.0.7/GSODR/DESCRIPTION | 12 +- GSODR-1.0.7/GSODR/MD5 | 26 ++-- GSODR-1.0.7/GSODR/NEWS.md | 28 ++++ GSODR-1.0.7/GSODR/R/GSODR-package.R |only GSODR-1.0.7/GSODR/R/get_GSOD.R | 32 +++-- GSODR-1.0.7/GSODR/README.md | 22 --- GSODR-1.0.7/GSODR/build/vignette.rds |binary GSODR-1.0.7/GSODR/inst/doc/GSODR.R | 115 ++++++++++--------- GSODR-1.0.7/GSODR/inst/doc/GSODR.Rmd | 144 +++++++++++++----------- GSODR-1.0.7/GSODR/inst/doc/GSODR.html | 92 ++++++--------- GSODR-1.0.7/GSODR/inst/extdata/country_list.rda |binary GSODR-1.0.7/GSODR/inst/extdata/isd_history.rda |binary GSODR-1.0.7/GSODR/man/GSODR.Rd | 2 GSODR-1.0.7/GSODR/vignettes/GSODR.Rmd | 144 +++++++++++++----------- 15 files changed, 337 insertions(+), 280 deletions(-)
Title: Multivariate Genomic Selection
Description: Estimating trait heritability and handling overfitting. This package includes a collection of functions for (1) estimating genetic variance-covariances and calculate trait heritability; and (2) handling overfitting by calculating the variance components and the heritability through cross validation.
Author: Zhenyu Jia
Maintainer: Zhenyu Jia <ajia.ucr@gmail.com>
Diff between GSMX versions 1.2 dated 2017-09-19 and 1.3 dated 2017-10-16
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- data/pseudo.data.rda |binary data/pseudo.kin.rda |binary man/GSMX-package.Rd | 12 ++++++------ man/gsm.Rd | 8 ++++---- 6 files changed, 19 insertions(+), 19 deletions(-)