Sequences encoding by using the chaos game representation. Löchel et al. (2019) <doi:10.1093/bioinformatics/btz493>.

This package provides a comprehensive R interface to access data from the Kraken cryptocurrency exchange REST API <https://docs.kraken.com/api/>. It allows users to retrieve various market data, such as asset information, trading pairs, and price data. The package is designed to facilitate efficient data access for analysis, strategy development, and monitoring of cryptocurrency market trends.

The kernel ridge regression and the gradient matching algorithm proposed in Niu et al. (2016) <https://proceedings.mlr.press/v48/niu16.html> and the warping algorithm proposed in Niu et al. (2017) <DOI:10.1007/s00180-017-0753-z> are implemented for parameter inference in differential equations. Four schemes are provided for improving parameter estimation in odes by using the odes regularisation and warping.

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>.

This package implements the Lilliefors-corrected Kolmogorov-Smirnov test for use in goodness-of-fit tests, suitable when population parameters are unknown and must be estimated by sample statistics. P-values are estimated by simulation. Can be used with a variety of continuous distributions, including normal, lognormal, univariate mixtures of normals, uniform, loguniform, exponential, gamma, and Weibull distributions. Functions to generate random numbers and calculate density, distribution, and quantile functions are provided for use with the log uniform and mixture distributions.

This package provides a toolkit for absolute and relative dating and analysis of chronological patterns. This package includes functions for chronological modeling and dating of archaeological assemblages from count data. It provides methods for matrix seriation. It also allows to compute time point estimates and density estimates of the occupation and duration of an archaeological site.

Restore underlining numeric data from rating history graph of KGS (an online platform of the game of go, <http://www.gokgs.com/>). A shiny application is also provided.

Multi-modal magnetic resonance imaging ('MRI') data from the Kirby21 reproducibility study <https://www.nitrc.org/projects/multimodal/>, including functional and structural imaging.

Kernel smoothing for Wishart random matrices described in Daayeb, Khardani and Ouimet (2025) <doi:10.48550/arXiv.2506.08816>, Gaussian and log-Gaussian models using least square or likelihood cross validation criteria for optimal bandwidth selection.

Kernel-based Tweedie compound Poisson gamma model using high-dimensional predictors for the analyses of zero-inflated response variables. The package features built-in estimation, prediction and cross-validation tools and supports choice of different kernel functions. For more details, please see Yi Lian, Archer Yi Yang, Boxiang Wang, Peng Shi & Robert William Platt (2023) <doi:10.1080/00401706.2022.2156615>.

Make computer vision tasks approachable in R by leveraging Large Language Models. Providing fine-tuned prompts, boilerplate functions, and input/output helpers for common computer vision workflows, such as classifying and describing images. Functions are designed to take images as input and return structured data, helping users build practical applications with minimal code.

An interactive document on the topic of K-nearest neighbour (KNN) using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://kartikeyabolar.shinyapps.io/KNNShiny/>.

Used to create dynamic, interactive D3.js based parallel coordinates and principal component plots in R'. The plots make visualizing k-means or other clusters simple and informative.

Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of RcppArmadillo to speed up the calculation of distances between observations.

This package provides a collection of personal helper functions to avoid redundancy in the spirit of the "Don't repeat yourself" principle of software development (<https://en.wikipedia.org/wiki/Don%27t_repeat_yourself>).

Most importantly, calculates Kullback-Leibler Divergence (KLD), Turing's perspective estimator and their confidence intervals.

An implementation of a simple and highly optimized ordinary kriging algorithm to plot geographical data.

This package implements the Kidney Failure Risk Equation (KFRE; Tangri and colleagues (2011) <doi:10.1001/jama.2011.451>; Tangri and colleagues (2016) <doi:10.1001/jama.2015.18202>) to compute 2- and 5-year kidney failure risk using 4-, 6-, and 8-variable models. Includes helpers to append risk columns to data frames, classify chronic kidney disease (CKD) stages and end-stage renal disease (ESRD) outcomes, and evaluate and plot model performance.

This package provides a wrapper for querying WISKI databases via the KiWIS REST API. WISKI is an SQL relational database used for the collection and storage of water data developed by KISTERS and KiWIS is a REST service that provides access to WISKI databases via HTTP requests (<https://www.kisters.eu/water-weather-and-environment/>). Contains a list of default databases (called hubs') and also allows users to provide their own KiWIS URL. Supports the entire query process- from metadata to specific time series values. All data is returned as tidy tibbles.

Access business registration data from the Dutch Chamber of Commerce (Kamer van Koophandel, KvK) through their official API <https://developers.kvk.nl/>. Search for companies by name, location, or registration number. Retrieve detailed business profiles, establishment information, and company name histories. Built on httr2 for robust API interaction with automatic pagination, error handling, and usage tracking.

To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.

The official TIMSS 2023 website provides the School Context Data Files for TIMSS 2023 Grade 4 in rdata format. However, the available data are presented solely in the form of numerical values. This package aims to transform the numerical data into categorical data, thereby enabling clearer interpretation and reducing ambiguity in statistical data analysis. Furthermore, the category labels are presented in Bahasa Indonesia. This initiative is intended as a contribution to promoting and expanding the use of Bahasa Indonesia in the field of programming, in line with its designation as one of the official languages of the United Nations General Assembly.

Given a set of points around a knee curve, analyzes first and second derivatives to find knee points.

This package implements methods for clustering mixed-type data, specifically combinations of continuous and nominal data. Special attention is paid to the often-overlooked problem of equitably balancing the contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method for clustering mixed-type data in the spirit of k-means clustering. It does not require dummy coding of variables, and is efficient enough to scale to rather large data sets. Also implemented is Modha-Spangler clustering, which uses a brute-force strategy to maximize the cluster separation simultaneously in the continuous and categorical variables. For more information, see Foss, Markatou, Ray, & Heching (2016) <doi:10.1007/s10994-016-5575-7> and Foss & Markatou (2018) <doi:10.18637/jss.v083.i13>.