Sun, 02 Mar 2025

Package renv updated to version 1.1.2 with previous version 1.1.1 dated 2025-02-07

Title: Project Environments
Description: A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.
Author: Kevin Ushey [aut, cre] , Hadley Wickham [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Kevin Ushey <kevin@rstudio.com>

Diff between renv versions 1.1.1 dated 2025-02-07 and 1.1.2 dated 2025-03-02

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Package vote updated to version 2.4-4 with previous version 2.4-3 dated 2023-12-10

Title: Election Vote Counting
Description: Counting election votes and determining election results by different methods, including the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round runoff methods (Raftery et al., 2021 <doi:10.32614/RJ-2021-086>).
Author: Hana Sevcikova [aut, cre], Bernard Silverman [aut], Adrian Raftery [aut]
Maintainer: Hana Sevcikova <hanas@uw.edu>

Diff between vote versions 2.4-3 dated 2023-12-10 and 2.4-4 dated 2025-03-02

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Package et.nwfva updated to version 0.2.0 with previous version 0.1.1 dated 2022-11-22

Title: Forest Yield Tables for Northwest Germany and their Application
Description: The new yield tables developed by the Northwest German Forest Research Institute (NW-FVA) provide a forest management tool for the five main commercial tree species oak, beech, spruce, Douglas-fir and pine for northwestern Germany. The new method applied for deriving yield tables combines measurements of growth and yield trials with growth simulations using a state-of-the-art single-tree growth simulator. By doing so, the new yield tables reflect the current increment level and the recommended graduated thinning from above is the underlying management concept. The yield tables are provided along with methods for deriving the site index and for interpolating between age and site indices and extrapolating beyond age and site index ranges. The inter-/extrapolations are performed traditionally by the rule of proportion or with a functional approach.
Author: Robert Nuske [aut, cre] , Kai Staupendahl [aut] , Matthias Albert [aut] , Nordwestdeutsche Forstliche Versuchsanstalt [cph, fnd]
Maintainer: Robert Nuske <robert.nuske@mailbox.org>

Diff between et.nwfva versions 0.1.1 dated 2022-11-22 and 0.2.0 dated 2025-03-02

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Package MetricGraph updated to version 1.4.1 with previous version 1.4.0 dated 2024-12-13

Title: Random Fields on Metric Graphs
Description: Facilitates creation and manipulation of metric graphs, such as street or river networks. Further facilitates operations and visualizations of data on metric graphs, and the creation of a large class of random fields and stochastic partial differential equations on such spaces. These random fields can be used for simulation, prediction and inference. In particular, linear mixed effects models including random field components can be fitted to data based on computationally efficient sparse matrix representations. Interfaces to the R packages 'INLA' and 'inlabru' are also provided, which facilitate working with Bayesian statistical models on metric graphs. The main references for the methods are Bolin, Simas and Wallin (2024) <doi:10.3150/23-BEJ1647>, Bolin, Kovacs, Kumar and Simas (2023) <doi:10.1090/mcom/3929> and Bolin, Simas and Wallin (2023) <doi:10.48550/arXiv.2304.03190> and <doi:10.48550/arXiv.2304.10372>.
Author: David Bolin [cre, aut], Alexandre Simas [aut], Jonas Wallin [aut]
Maintainer: David Bolin <davidbolin@gmail.com>

Diff between MetricGraph versions 1.4.0 dated 2024-12-13 and 1.4.1 dated 2025-03-02

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Package offsetreg updated to version 1.1.1 with previous version 1.1.0 dated 2024-04-11

Title: An Extension of 'Tidymodels' Supporting Offset Terms
Description: Extend the 'tidymodels' ecosystem <https://www.tidymodels.org/> to enable the creation of predictive models with offset terms. Models with offsets are most useful when working with count data or when fitting an adjustment model on top of an existing model with a prior expectation. The former situation is common in insurance where data is often weighted by exposures. The latter is common in life insurance where industry mortality tables are often used as a starting point for setting assumptions.
Author: Matt Heaphy [aut, cre, cph]
Maintainer: Matt Heaphy <mattrmattrs@gmail.com>

Diff between offsetreg versions 1.1.0 dated 2024-04-11 and 1.1.1 dated 2025-03-02

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Package sampcompR updated to version 0.3.0 with previous version 0.2.6 dated 2024-12-08

Title: Comparing and Visualizing Differences Between Surveys
Description: Easily analyze and visualize differences between samples (e.g., benchmark comparisons, nonresponse comparisons in surveys) on three levels. The comparisons can be univariate, bivariate or multivariate. On univariate level the variables of interest of a survey and a comparison survey (i.e. benchmark) are compared, by calculating one of several difference measures (e.g., relative difference in mean), and an average difference between the surveys. On bivariate level a function can calculate significant differences in correlations for the surveys. And on multivariate levels a function can calculate significant differences in model coefficients between the surveys of comparison. All of those differences can be easily plotted and outputted as a table. For more detailed information on the methods and example use see Rohr, B., Silber, H., & Felderer, B. (2024). Comparing the Accuracy of Univariate, Bivariate, and Multivariate Estimates across Probability and Nonprobability Surveys with Po [...truncated...]
Author: Bjoern Rohr [aut, cre, cph], Barbara Felderer [aut]
Maintainer: Bjoern Rohr <bjoern.rohr@gesis.org>

Diff between sampcompR versions 0.2.6 dated 2024-12-08 and 0.3.0 dated 2025-03-02

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Package popsom7 updated to version 7.1.0 with previous version 7.0.0 dated 2025-02-19

Title: A Fast, User-Friendly Implementation of Self-Organizing Maps (SOMs)
Description: Methods for building self-organizing maps (SOMs) with a number of distinguishing features such automatic centroid detection and cluster visualization using starbursts. For more details see the paper "Improved Interpretability of the Unified Distance Matrix with Connected Components" by Hamel and Brown (2011) in <ISBN:1-60132-168-6>. The package provides user-friendly access to two models we construct: (a) a SOM model and (b) a centroid based clustering model. The package also exposes a number of quality metrics for the quantitative evaluation of the map, Hamel (2016) <doi:10.1007/978-3-319-28518-4_4>. Finally, we reintroduced our fast, vectorized training algorithm for SOM with substantial improvements. It is about an order of magnitude faster than the canonical, stochastic C implementation <doi:10.1007/978-3-030-01057-7_60>.
Author: Lutz Hamel [aut, cre], Benjamin Ott [aut], Gregory Breard [aut], Robert Tatoian [aut], Michael Eiger [aut], Vishakh Gopu [aut]
Maintainer: Lutz Hamel <lutzhamel@uri.edu>

Diff between popsom7 versions 7.0.0 dated 2025-02-19 and 7.1.0 dated 2025-03-02

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Package greeks updated to version 1.4.4 with previous version 1.4.3 dated 2024-09-17

Title: Sensitivities of Prices of Financial Options and Implied Volatilities
Description: Methods to calculate sensitivities of financial option prices for European, geometric and arithmetic Asian, and American options, with various payoff functions in the Black Scholes model, and in more general jump diffusion models. A shiny app to interactively plot the results is included. Furthermore, methods to compute implied volatilities are provided for a wide range of option types and custom payoff functions. Classical formulas are implemented for European options in the Black Scholes Model, as is presented in Hull, J. C. (2017), Options, Futures, and Other Derivatives. In the case of Asian options, Malliavin Monte Carlo Greeks are implemented, see Hudde, A. & Rüschendorf, L. (2023). European and Asian Greeks for exponential Lévy processes. <doi:10.1007/s11009-023-10014-5>. For American options, the Binomial Tree Method is implemented, as is presented in Hull, J. C. (2017).
Author: Anselm Hudde [aut, cre]
Maintainer: Anselm Hudde <anselmhudde@gmx.de>

Diff between greeks versions 1.4.3 dated 2024-09-17 and 1.4.4 dated 2025-03-02

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Package quickcode updated to version 1.0.6 with previous version 1.0.5 dated 2025-02-03

Title: Quick and Essential 'R' Tricks for Better Scripts
Description: The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to improve your scripts. Improve the quality and reproducibility of 'R' scripts.
Author: Obinna Obianom [aut, cre], Brice Richard [aut]
Maintainer: Obinna Obianom <idonshayo@gmail.com>

Diff between quickcode versions 1.0.5 dated 2025-02-03 and 1.0.6 dated 2025-03-02

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Package pmetar updated to version 0.5.1 with previous version 0.5.0 dated 2023-10-25

Title: Processing METAR Weather Reports
Description: Allows to download current and historical METAR weather reports extract and parse basic parameters and present main weather information. Current reports are downloaded from Aviation Weather Center <https://aviationweather.gov/data/metar/> and historical reports from Iowa Environmental Mesonet web page of Iowa State University ASOS-AWOS-METAR <http://mesonet.agron.iastate.edu/AWOS/>.
Author: Pawel Cwiek [aut, cre], David Megginson [ctb] , Greg Thompson [ctb]
Maintainer: Pawel Cwiek <prc.altodato@gmail.com>

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Package NeuralEstimators updated to version 0.2.0 with previous version 0.1.3 dated 2025-01-14

Title: Likelihood-Free Parameter Estimation using Neural Networks
Description: An 'R' interface to the 'Julia' package 'NeuralEstimators.jl'. The package facilitates the user-friendly development of neural Bayes estimators, which are neural networks that map data to a point summary of the posterior distribution (Sainsbury-Dale et al., 2024, <doi:10.1080/00031305.2023.2249522>). These estimators are likelihood-free and amortised, in the sense that, once the neural networks are trained on simulated data, inference from observed data can be made in a fraction of the time required by conventional approaches. The package also supports amortised Bayesian or frequentist inference using neural networks that approximate the posterior or likelihood-to-evidence ratio (Zammit-Mangion et al., 2025, Sec. 3.2, 5.2, <doi:10.48550/arXiv.2404.12484>). The package accommodates any model for which simulation is feasible by allowing users to define models implicitly through simulated data.
Author: Matthew Sainsbury-Dale [aut, cre]
Maintainer: Matthew Sainsbury-Dale <msainsburydale@gmail.com>

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Package ggsurveillance updated to version 0.2.0 with previous version 0.1.2 dated 2025-02-11

Title: Tools for Outbreak Investigation/Infectious Disease Surveillance
Description: Create epicurves or epigantt charts in 'ggplot2'. Prepare data for visualisation or other reporting for infectious disease surveillance and outbreak investigation. Includes tidy functions to solve date based transformations for common reporting tasks, like (A) seasonal date alignment for respiratory disease surveillance, (B) date-based case binning based on specified time intervals like isoweek, epiweek, month and more, (C) automated detection and marking of the new year based on the date/datetime axis of the 'ggplot2'. An introduction on how to use epicurves can be found on the US CDC website (2012, <https://www.cdc.gov/training/quicklearns/epimode/index.html>).
Author: Alexander Bartel [aut, cre]
Maintainer: Alexander Bartel <alexander.bartel@fu-berlin.de>

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Package seqtrie updated to version 0.2.9 with previous version 0.2.8 dated 2024-05-04

Title: Radix Tree and Trie-Based String Distances
Description: A collection of Radix Tree and Trie algorithms for finding similar sequences and calculating sequence distances (Levenshtein and other distance metrics). This work was inspired by a trie implementation in Python: "Fast and Easy Levenshtein distance using a Trie." Hanov (2011) <https://stevehanov.ca/blog/index.php?id=114>.
Author: Travers Ching [aut, cre, cph], Martin Moene [ctb, cph] , Steve Hanov [ctb] , Martin Leitner-Ankerl [ctb]
Maintainer: Travers Ching <traversc@gmail.com>

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Package OpenRepGrid updated to version 0.1.17 with previous version 0.1.16 dated 2024-12-02

Title: Tools to Analyze Repertory Grid Data
Description: Analyze repertory grids, a qualitative-quantitative data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across various domains ranging from clinical psychology to marketing. The package contains functions to quantitatively analyze and visualize repertory grid data (e.g. 'Fransella', 'Bell', & 'Bannister', 2004, ISBN: 978-0-470-09080-0). The package is part of the The package is part of the <https://openrepgrid.org/> project.
Author: Mark Heckmann [aut, cre, cph] , Alejandro Garcia Gutierrez [ctb], Diego Vitali [ctb]
Maintainer: Mark Heckmann <heckmann.mark@gmail.com>

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Package PSweight updated to version 2.1.1 with previous version 2.1.0 dated 2025-02-12

Title: Propensity Score Weighting for Causal Inference with Observational Studies and Randomized Trials
Description: Supports propensity score weighting analysis of observational studies and randomized trials. Enables the estimation and inference of average causal effects with binary and multiple treatments using overlap weights (ATO), inverse probability of treatment weights (ATE), average treatment effect among the treated weights (ATT), matching weights (ATM) and entropy weights (ATEN), with and without propensity score trimming. These weights are members of the family of balancing weights introduced in Li, Morgan and Zaslavsky (2018) <doi:10.1080/01621459.2016.1260466> and Li and Li (2019) <doi:10.1214/19-AOAS1282>.
Author: Tianhui Zhou [aut], Guangyu Tong [aut], Fan Li [aut], Laine Thomas [aut], Fan Li [aut], Yukang Zeng [cre]
Maintainer: Yukang Zeng <yukang.zeng@yale.edu>

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