Conditional logistic regression with longitudinal follow up and individual-level random coefficients: A stable and efficient two-step estimation method.

This package provides triangulations of regular height fields, based on the methods described in "Fast Polygonal Approximation of Terrains and Height Fields" Michael Garland and Paul S. Heckbert (1995) <https://www.mgarland.org/files/papers/scape.pdf> using code from the hmm library written by Michael Fogleman <https://github.com/fogleman/hmm>.

This package provides a system built on tidymodels for generating synthetic tabular data. We provide tools for ordering a sequential synthesis, feature and target engineering, sampling, hyperparameter tuning, enforcing constraints, and adding extra noise during a synthesis.

Perform test to detect differences in structure between families of trees. The method is based on cophenetic distances and aggregated Student's tests.

Taxonomic lists matching and merging, casting and melting scientific names, managing taxonomic lists from Global Biodiversity Information Facility GBIF <https://www.gbif.org/> or Integrated Taxonomic Information System ITIS', <https://itis.gov/> harvesting names from Wikipedia and fuzzy matching.

This package provides tidyverse methods for wrangling and analyzing Earth Engine <https://earthengine.google.com/> data. These methods help the user with filtering, joining and summarising Earth Engine image collections.

Create "good enough" tables with a single formula. tablespan tables can be exported to Excel', HTML', LaTeX', and RTF by leveraging the packages openxlsx and gt'. See <https://jhorzek.github.io/tablespan/> for an introduction.

Additive hazards models with two stage residual inclusion method are fitted under either survival data or competing risks data. The estimator incorporates an instrumental variable and therefore can recover causal estimand in the presence of unmeasured confounding under some assumptions. A.Ying, R. Xu and J. Murphy. (2019) <doi:10.1002/sim.8071>.

This package provides a toolkit for working with TOML files in R while preserving formatting, comments, and structure. tomledit enables serialization of R objects such as lists, data.frames, numeric, logical, and date vectors.

This package creates simulated clinical trial data with realistic correlation structures and assumed efficacy levels by using a tilted bootstrap resampling approach. Samples are drawn from observed data with some samples appearing more frequently than others. May also be used for simulating from a joint Bayesian distribution along with clinical trials based on the Bayesian distribution.

Our method introduces mathematically well-defined measures for tightness of branches in a hierarchical tree. Statistical significance of the findings is determined, for all branches of the tree, by performing permutation tests, optionally with generalized Pareto p-value estimation.

This package provides a framework to work with decision rules. Rules can be extracted from supported models, augmented with (custom) metrics using validation data, manipulated using standard dataframe operations, reordered and pruned based on a metric, predict on unseen (test) data. Utilities include; Creating a rulelist manually, Exporting a rulelist as a SQL case statement and so on. The package offers two classes; rulelist and ruleset based on dataframe.

This package provides a geomorphology-based hydrological modelling for transferring streamflow measurements from gauged to ungauged catchments. Inverse modelling enables to estimate net rainfall from streamflow measurements following Boudhraâ et al. (2018) <doi:10.1080/02626667.2018.1425801>. Resulting net rainfall is then estimated on the ungauged catchments by spatial interpolation in order to finally simulate streamflow following de Lavenne et al. (2016) <doi:10.1002/2016WR018716>.

Reconstructs animal tracks from magnetometer, accelerometer, depth and optional speed data. Designed primarily using data from Wildlife Computers Daily Diary tags deployed on northern fur seals.

Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.

Several datasets which describe the chef contestants in Top Chef, the challenges that they compete in, and the results of those challenges. This data is useful for practicing data wrangling, graphing, and analyzing how each season of Top Chef played out.

Easily construct prompts and associated logic for interacting with large language models (LLMs). tidyprompt introduces the concept of prompt wraps, which are building blocks that you can use to quickly turn a simple prompt into a complex one. Prompt wraps do not just modify the prompt text, but also add extraction and validation functions that will be applied to the response of the LLM. This ensures that the user gets the desired output. tidyprompt can add various features to prompts and their evaluation by LLMs, such as structured output, automatic feedback, retries, reasoning modes, autonomous R function calling, and R code generation and evaluation. It is designed to be compatible with any LLM provider that offers chat completion.

The general principle relies on calculating the cumulative signal of nascent RNA sequencing over the gene body of any given gene or transcription unit. tepr can identify transcription attenuation sites by comparing profile to a null model which assumes uniform read density over the entirety of the transcription unit. It can also identify increased or diminished transcription attenuation by comparing two conditions. Besides rigorous statistical testing and high sensitivity, a major feature of tepr is its ability to provide the elongation pattern of each individual gene, including the position of the main attenuation point when such a phenomenon occurs. Using tepr', users can visualize and refine genome-wide aggregated analyses of elongation patterns to robustly identify effects specific to subsets of genes. These metrics are suitable for internal comparisons (between genes in each condition) and for studying elongation of the same gene in different conditions or comparing it to a perfect theoretical uniform elongation.

Use SQL SELECT statements to query R data frames.

This package provides a Tcl/Tk Graphical User Interface (GUI) to display images than can be zoomed and panned using the mouse and keyboard shortcuts. tkImgR read and write different image formats (PPM/PGM, PNG and GIF) using the standard Tcl/Tk distribution (>=8.6), but other formats (JPEG, TIFF, CR2) can be handled using the tkImg package for Tcl/Tk'.

Agglomerative hierarchical clustering with a bespoke distance measure based on medication similarities in the Anatomical Therapeutic Chemical Classification System, medication timing and medication amount or dosage. Tools for summarizing, illustrating and manipulating the cluster objects are also available.

R implementation of the software tools developed in the H-CUP (Healthcare Cost and Utilization Project) <https://hcup-us.ahrq.gov> and AHRQ (Agency for Healthcare Research and Quality) <https://www.ahrq.gov>. It currently contains functions for mapping ICD-9 codes to the AHRQ comorbidity measures and translating ICD-9 (resp. ICD-10) codes to ICD-10 (resp. ICD-9) codes based on GEM (General Equivalence Mappings) from CMS (Centers for Medicare and Medicaid Services).

This package provides 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.

This package provides functions for interacting directly with the Taiwan Economic Journal API to offer data in R. For more information go to <https://api.tej.com.tw>.