Title: Vehicular Emissions Inventories
Description: Elaboration of vehicular emissions inventories,
consisting in four stages, pre-processing activity data, preparing
emissions factors, estimating the emissions and post-processing of emissions
in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>.
Before using VEIN you need to know the vehicular composition of your study area, in other words,
the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to
start with the project to download a template to create a structure of directories and scripts.
Author: Sergio Ibarra-Espinosa [aut, cre] ,
Daniel Schuch [ctb] ,
Joao Bazzo [ctb] ,
Mario Gavidia-Calderon [ctb] ,
Karl Ropkins [ctb]
Maintainer: Sergio Ibarra-Espinosa <zergioibarra@gmail.com>
Diff between vein versions 1.3.0 dated 2025-03-29 and 1.5.0 dated 2025-10-04
DESCRIPTION | 23 ++++++++-------- MD5 | 18 ++++++------- NEWS.md | 17 +++++++++++- R/dmonth.R | 7 +++-- R/speciate.R | 70 ++++++++++++++++++++++++++++++++++++++++----------- R/sysdata.rda |binary build/partial.rdb |binary build/vignette.rds |binary inst/doc/basics.html | 9 +++--- man/speciate.Rd | 18 ++++++++++--- 10 files changed, 118 insertions(+), 44 deletions(-)
Title: Stepwise Clustered Ensemble
Description: Implementation of Stepwise Clustered Ensemble (SCE) and Stepwise Cluster Analysis (SCA) for multivariate data analysis. The package provides comprehensive tools for feature selection, model training, prediction, and evaluation in hydrological and environmental modeling applications. Key functionalities include recursive feature elimination (RFE), Wilks feature importance analysis, model validation through out-of-bag (OOB) validation, and ensemble prediction capabilities. The package supports both single and multivariate response variables, making it suitable for complex environmental modeling scenarios. For more details see Li et al. (2021) <doi:10.5194/hess-25-4947-2021>.
Author: Kailong Li [aut, cre]
Maintainer: Kailong Li <lkl98509509@gmail.com>
Diff between SCE versions 1.1.1 dated 2025-07-25 and 1.1.2 dated 2025-10-04
DESCRIPTION | 6 +++--- MD5 | 17 +++++++++-------- NAMESPACE | 1 + NEWS.md | 14 ++++++++++++++ R/SCA.R | 4 ++-- R/SCE.R | 4 ++-- R/Wilks_importance.R | 7 +++++-- README.md | 6 +++--- man/importance.Rd | 7 ++++--- man/summary.Rd |only 10 files changed, 43 insertions(+), 23 deletions(-)
Title: Cast '(R)Markdown' Files to 'XML' and Back Again
Description: Parsing '(R)Markdown' files with numerous regular expressions can
be fraught with peril, but it does not have to be this way. Converting
'(R)Markdown' files to 'XML' using the 'commonmark' package allows
in-memory editing via of 'markdown' elements via 'XPath' through the
extensible 'R6' class called 'yarn'. These modified 'XML' representations
can be written to '(R)Markdown' documents via an 'xslt' stylesheet which
implements an extended version of 'GitHub'-flavoured 'markdown' so that you
can tinker to your hearts content.
Author: Maelle Salmon [aut] ,
Zhian N. Kamvar [aut, cre] ,
Jeroen Ooms [aut],
Nick Wellnhofer [cph] ,
rOpenSci [fnd] ,
Peter Daengeli [ctb]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>
Diff between tinkr versions 0.3.0 dated 2025-05-03 and 0.3.1 dated 2025-10-04
DESCRIPTION | 7 + MD5 | 62 ++++++++-------- NEWS.md | 34 +++++---- R/add_md.R | 47 ++++++++---- R/asis-nodes.R | 45 ++++++------ R/attr-nodes.R | 16 +--- R/class-yarn.R | 4 - R/find_between.R | 11 ++ R/get_protected.R | 16 ++-- R/resolve-links.R | 59 +++++++++------ R/show.R | 43 +++++++---- R/stylesheet.R | 9 +- R/to_md.R | 74 ++++++++++--------- R/to_xml.R | 17 ++-- R/utils.R | 33 +++++--- build/vignette.rds |binary inst/scripts/roweb2_headers.R | 22 ++--- inst/stylesheets/xml2md_gfm.xsl | 3 man/find_between.Rd | 2 man/get_protected.Rd | 4 - man/resolve_anchor_links.Rd | 4 - tests/testthat/_snaps/to_md.md | 38 ++++++++++ tests/testthat/test-anchor-links.R | 3 tests/testthat/test-asis-nodes.R | 25 ++---- tests/testthat/test-attr-nodes.R | 2 tests/testthat/test-class-yarn.R | 135 +++++++++++++++++++++--------------- tests/testthat/test-get_protected.R | 13 +-- tests/testthat/test-show.R | 35 +++------ tests/testthat/test-to_md.R | 125 +++++++++++++++++++++++++-------- tests/testthat/test-to_xml.R | 20 +---- tests/testthat/test-utils-string.R | 1 tests/testthat/test-utils.R | 22 +++++ 32 files changed, 566 insertions(+), 365 deletions(-)
Title: Plant Photobiology Related Functions and Data
Description: Provides functions for quantifying visible (VIS) and ultraviolet
(UV) radiation in relation to the photoreceptors Phytochromes,
Cryptochromes, and UVR8 which are present in plants. It also includes data
sets on the optical properties of plants. Part of the 'r4photobiology'
suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>
Diff between photobiologyPlants versions 0.6.1 dated 2025-09-24 and 0.6.1-1 dated 2025-10-04
DESCRIPTION | 12 ++++++------ MD5 | 8 ++++---- NEWS.md | 6 ++++++ inst/doc/r4p-introduction.html | 2 +- inst/doc/user-guide.html | 6 +++--- 5 files changed, 20 insertions(+), 14 deletions(-)
More information about photobiologyPlants at CRAN
Permanent link
Title: Automation and Standardization of Cleaning Clinical Laboratory
Data
Description: Navigating the shift of clinical laboratory data from primary everyday clinical use to secondary research purposes presents a significant challenge. Given the substantial time and expertise required for lab data pre-processing and cleaning and the lack of all-in-one tools tailored for this need, we developed our algorithm 'lab2clean' as an open-source R-package. 'lab2clean' package is set to automate and standardize the intricate process of cleaning clinical laboratory results. With a keen focus on improving the data quality of laboratory result values and units, our goal is to equip researchers with a straightforward, plug-and-play tool, making it smoother for them to unlock the true potential of clinical laboratory data in clinical research and clinical machine learning (ML) model development. Functions to clean & validate result values (Version 1.0) are described in detail in 'Zayed et al. (2024)' <doi:10.1186/s12911-024-02652-7>. Functions to standardize & harmonize r [...truncated...]
Author: Ahmed Zayed [aut, cre] ,
Ilias Sarikakis [aut, ctb],
Arne Janssens [aut, ctb],
Pavlos Mamouris [ctb]
Maintainer: Ahmed Zayed <ahmed.zayed@kuleuven.be>
Diff between lab2clean versions 1.0.0 dated 2024-09-09 and 2.0.0 dated 2025-10-04
DESCRIPTION | 28 MD5 | 66 + NAMESPACE | 2 R/F1_clean_lab_result_V7.R | 1581 +++++++++++++++++++-------------------- R/F2_validate_lab_result_V3.R | 590 +++++++------- R/F3_standardize_lab_unit_V7.R |only R/F4_harmonize_lab_unit_V5.R |only R/Function_1_dummy.R | 30 R/Function_2_dummy.R | 36 R/Function_3_dummy.R |only R/Function_4_dummy.R |only R/RWD_units_to_UCUM_V2.R |only R/annotable_strings.R |only R/common_words.R | 44 - R/logic_rules.R | 34 R/loinc_reference_unit_v1.R |only R/parseUnit_function_V4.R |only R/parsed_units_df.R |only R/reportable_interval.R | 34 build/vignette.rds |binary data/Function_3_dummy.rda |only data/Function_4_dummy.rda |only data/RWD_units_to_UCUM_V2.rda |only data/annotable_strings.rda |only data/loinc_reference_unit_v1.rda |only data/parsed_units_df.rda |only inst/doc/lab2clean.R | 105 +- inst/doc/lab2clean.Rmd | 629 +++++++++------ inst/doc/lab2clean.html | 1001 ++++++++++++++++++++++-- man/Function_1_dummy.Rd | 6 man/Function_2_dummy.Rd | 12 man/Function_3_dummy.Rd |only man/Function_4_dummy.Rd |only man/RWD_units_to_UCUM_V2.Rd |only man/annotable_strings.Rd |only man/clean_lab_result.Rd | 32 man/common_words.Rd | 20 man/harmonize_lab_unit.Rd |only man/logic_rules.Rd | 10 man/loinc_reference_unit_v1.Rd |only man/parseUnit.Rd |only man/parsed_units_df.Rd |only man/reportable_interval.Rd | 10 man/standardize_lab_unit.Rd |only man/validate_lab_result.Rd | 44 - vignettes/lab2clean.Rmd | 629 +++++++++------ 46 files changed, 3027 insertions(+), 1916 deletions(-)
Title: Descriptive Statistics and Data Management Tools
Description: Extracts and summarizes metadata from data frames, including variable names, labels, types, and missing values. Computes compact descriptive statistics, frequency tables, and cross-tabulations to assist with efficient data exploration. Facilitates the identification of missing data patterns and structural issues in datasets. Designed to streamline initial data management and exploratory analysis workflows within 'R'.
Author: Amal Tawfik [aut, cre, cph]
Maintainer: Amal Tawfik <amal.tawfik@hesav.ch>
Diff between spicy versions 0.2.0 dated 2025-09-25 and 0.2.1 dated 2025-10-04
DESCRIPTION | 6 - MD5 | 16 +- NAMESPACE | 3 NEWS.md | 4 R/copy_clipboard.R | 276 ++++++++++++++++++++++++------------------------ R/label_from_names.R | 42 ++++--- R/spicy-package.R | 69 ++++++------ README.md | 22 +++ man/label_from_names.Rd | 4 9 files changed, 242 insertions(+), 200 deletions(-)
Title: Bayesian Analysis of Networks of Binary and/or Ordinal Variables
Description: Bayesian variable selection methods for analyzing the structure of a Markov random field model for a network of binary and/or ordinal variables.
Author: Maarten Marsman [aut, cre] ,
Giuseppe Arena [ctb] ,
Karoline Huth [ctb] ,
Nikola Sekulovski [ctb] ,
Don van den Bergh [ctb]
Maintainer: Maarten Marsman <m.marsman@uva.nl>
Diff between bgms versions 0.1.6.0 dated 2025-09-27 and 0.1.6.1 dated 2025-10-04
DESCRIPTION | 8 ++-- MD5 | 63 ++++++++++++++++++----------------- NAMESPACE | 2 + NEWS.md | 14 +++++++ R/bgm.R | 48 +++++++++++++++++++++------ R/bgmCompare.R | 48 +++++++++++++++++++++++---- R/extractor_functions.R | 64 +++++++++++++++++++++++++++++++++++- R/mcmc_summary.R | 3 + build/partial.rdb |binary inst/CITATION | 4 +- man/bgm.Rd | 9 +---- man/bgmCompare.Rd | 5 +- man/extractor_functions.Rd | 7 +++ src/Makevars.in | 2 - src/bgmCompare_helper.cpp | 2 - src/bgmCompare_logp_and_grad.cpp | 2 - src/bgmCompare_parallel.cpp | 1 src/bgmCompare_sampler.cpp | 3 - src/bgm_helper.cpp | 2 - src/bgm_logp_and_grad.cpp | 2 - src/bgm_parallel.cpp | 69 ++++++++++++++++++--------------------- src/bgm_sampler.cpp | 35 +++++++++---------- src/bgm_sampler.h | 5 +- src/chainResults.h |only src/mcmc_adaptation.h | 4 +- src/mcmc_hmc.cpp | 1 src/mcmc_leapfrog.cpp | 2 - src/mcmc_nuts.cpp | 2 - src/mcmc_rwm.cpp | 2 - src/mcmc_rwm.h | 1 src/mcmc_utils.cpp | 2 - src/progress_manager.cpp | 30 ++++++++++------ src/sbm_edge_prior.cpp | 2 - 33 files changed, 287 insertions(+), 157 deletions(-)
Title: Nonlinear Nonparametric Statistics
Description: NNS (Nonlinear Nonparametric Statistics) leverages partial moments – the fundamental elements of variance that asymptotically approximate the area under f(x) – to provide a robust foundation for nonlinear analysis while maintaining linear equivalences. NNS delivers a comprehensive suite of advanced statistical techniques, including: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization, Stochastic dominance and Advanced Monte Carlo sampling. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole [aut, cre],
Roberto Spadim [ctb]
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>
Diff between NNS versions 11.6.1 dated 2025-10-02 and 11.6.2 dated 2025-10-04
DESCRIPTION | 8 +- MD5 | 14 ++-- R/Dependence.R | 17 ++--- R/Regression.R | 4 - README.md | 4 - inst/doc/NNSvignette_Classification.html | 52 +++++++++------ inst/doc/NNSvignette_Overview.html | 104 +++++++++++++++++++------------ src/fast_lm.cpp | 87 ++++++++++++++----------- 8 files changed, 169 insertions(+), 121 deletions(-)
Title: Broadcasted Array Operations Like 'NumPy'
Description: Implements efficient 'NumPy'-like broadcasted operations for atomic and recursive arrays.
In the context of operations involving 2 (or more) arrays,
“broadcasting” refers to efficiently recycling array dimensions without allocating additional memory.
Besides linking to 'Rcpp',
'broadcast' does not use any external libraries in any way;
'broadcast' was essentially made from scratch and can be installed out-of-the-box.
The implementations available in 'broadcast' include, but are not limited to, the following.
1) Broadcasted element-wise operations on any 2 arrays;
they support a large set of
relational, arithmetic, Boolean, string, and bit-wise operations.
2) A faster, more memory efficient, and broadcasted abind-like function,
for binding arrays along an arbitrary dimension.
3) Broadcasted ifelse-like, and apply-like functions.
4) Casting functions,
that cast subset-groups of an array to a new dimension, cast nested lists to dimensional lists, and vice-versa.
5) A few linear algebra fu [...truncated...]
Author: Tony Wilkes [aut, cre, cph]
Maintainer: Tony Wilkes <tony_a_wilkes@outlook.com>
Diff between broadcast versions 0.1.5 dated 2025-10-02 and 0.1.5.1 dated 2025-10-04
DESCRIPTION | 6 MD5 | 37 +- NEWS.md | 6 R/acast.R | 2 R/bc_b.R | 10 R/bc_bit.R | 15 R/bc_cplx.R | 13 R/bc_d.R | 12 R/bc_i.R | 13 R/bc_ifelse.R | 159 ++++---- R/bc_list.R | 11 R/bc_raw.R | 11 R/bc_rel.R | 14 R/bc_str.R | 17 R/bcapply.R | 156 ++++---- R/internal_cast.R | 11 inst/tinytest/test-S4error-callerenv.R |only inst/tinytest/test-binary_errors.R | 4 src/broadcast.h | 602 --------------------------------- src/rcpp_bc_b.cpp | 22 - 20 files changed, 282 insertions(+), 839 deletions(-)
Title: Bayesian Geostatistics Using Predictive Stacking
Description: Fits Bayesian hierarchical spatial and spatial-temporal process
models for point-referenced Gaussian, Poisson, binomial, and binary data
using stacking of predictive densities. It involves sampling from
analytically available posterior distributions conditional upon candidate
values of the spatial process parameters and, subsequently assimilate
inference from these individual posterior distributions using Bayesian
predictive stacking. Our algorithm is highly parallelizable and hence, much
faster than traditional Markov chain Monte Carlo algorithms while delivering
competitive predictive performance. See Zhang, Tang, and Banerjee (2025)
<doi:10.1080/01621459.2025.2566449>, and, Pan, Zhang, Bradley, and Banerjee
(2025) <doi:10.48550/arXiv.2406.04655> for details.
Author: Soumyakanti Pan [aut, cre] ,
Sudipto Banerjee [aut]
Maintainer: Soumyakanti Pan <span18@ucla.edu>
Diff between spStack versions 1.1.1 dated 2025-07-14 and 1.1.2 dated 2025-10-04
DESCRIPTION | 8 ++++---- MD5 | 38 +++++++++++++++++++------------------- NEWS.md | 4 ++++ R/spGLMexact.R | 4 ++-- R/spGLMstack.R | 4 ++-- R/spLMstack.R | 8 ++++---- R/spStack-package.R | 8 ++++---- R/stvcGLMexact.R | 4 ++-- R/stvcGLMstack.R | 2 +- README.md | 2 +- inst/doc/spStack.html | 3 ++- inst/doc/spatial.html | 4 ++-- inst/doc/technical_overview.html | 3 ++- man/spGLMexact.Rd | 4 ++-- man/spGLMstack.Rd | 4 ++-- man/spLMstack.Rd | 8 ++++---- man/spStack-package.Rd | 8 ++++---- man/stvcGLMexact.Rd | 4 ++-- man/stvcGLMstack.Rd | 2 +- vignettes/refs.bib | 9 +++++---- 20 files changed, 69 insertions(+), 62 deletions(-)
Title: Applies Display Metadata to Analysis Results Datasets
Description: Creates a framework to store and apply display metadata to
Analysis Results Datasets (ARDs). The use of 'tfrmt' allows users to
define table format and styling without the data, and later apply the
format to the data.
Author: Becca Krouse [aut, cre],
Christina Fillmore [aut] ,
Ellis Hughes [aut] ,
Karima Ahmad [aut] ,
Shannon Haughton [aut],
Dragoș Moldovan-Gruenfeld [aut],
GlaxoSmithKline Research & Development Limited [cph, fnd],
Atorus Research LLC [cph, fnd]
Maintainer: Becca Krouse <becca.z.krouse@gsk.com>
Diff between tfrmt versions 0.2.0 dated 2025-09-06 and 0.2.1 dated 2025-10-04
tfrmt-0.2.0/tfrmt/tests/testthat/test-big_ns.R |only tfrmt-0.2.1/tfrmt/DESCRIPTION | 10 tfrmt-0.2.1/tfrmt/MD5 | 31 +- tfrmt-0.2.1/tfrmt/NAMESPACE | 2 tfrmt-0.2.1/tfrmt/NEWS.md | 7 tfrmt-0.2.1/tfrmt/R/JSON.R | 2 tfrmt-0.2.1/tfrmt/R/apply_footnote_meta.R | 2 tfrmt-0.2.1/tfrmt/R/apply_footnote_plan.R | 19 - tfrmt-0.2.1/tfrmt/R/apply_frmt_methods.R | 3 tfrmt-0.2.1/tfrmt/R/big_n.R | 240 +++++++++++-------- tfrmt-0.2.1/tfrmt/R/frmt_plans.R | 2 tfrmt-0.2.1/tfrmt/R/frmt_utils.R | 7 tfrmt-0.2.1/tfrmt/R/print_to_gt.R | 11 tfrmt-0.2.1/tfrmt/man/big_n_structure.Rd | 22 - tfrmt-0.2.1/tfrmt/tests/testthat/_snaps/big_n.md |only tfrmt-0.2.1/tfrmt/tests/testthat/_snaps/prep_card.md | 1 tfrmt-0.2.1/tfrmt/tests/testthat/test-big_n.R |only tfrmt-0.2.1/tfrmt/tests/testthat/test-col_plan.R | 30 +- 18 files changed, 230 insertions(+), 159 deletions(-)