Integrates several popular high-dimensional methods based on Linear Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification as mentioned in Yuqing Pan, Qing Mai and Xin Zhang (2019) <arXiv:1904.03469>. Functions are included for covariate adjustment, model fitting, cross validation and prediction.

The twelvedata REST service offers access to current and historical data on stocks, standard as well as digital crypto currencies, and other financial assets covering a wide variety of course and time spans. See <https://twelvedata.com/> for details, to create an account, and to request an API key for free-but-capped access to the data.

Estimates the time-varying (tv) parameters of the GARCH(1,1) model, enabling the modeling of non-stationary volatilities by allowing the model parameters to change gradually over time. The estimation and prediction processes are facilitated through the application of the Kalman filter and state-space equations. This package supports the estimation of tv parameters for various deterministic functions, which can be identified through exploratory analysis of different time periods or segments of return data. The methodology is grounded in the framework presented by Ferreira et al. (2017) <doi:10.1080/00949655.2017.1334778>.

Prediction intervals for ARIMA and structural time series models using importance sampling approach with uninformative priors for model parameters, leading to more accurate coverage probabilities in frequentist sense. Instead of sampling the future observations and hidden states of the state space representation of the model, only model parameters are sampled, and the method is based solving the equations corresponding to the conditional coverage probability of the prediction intervals. This makes method relatively fast compared to for example MCMC methods, and standard errors of prediction limits can also be computed straightforwardly.

The tabularmap is one of the visualization methods for efficiently displaying data consisting of multiple elements by tiling them. When dealing with geospatial, it corrects for differences in visibility between areas.

This package provides conditional maximum likelihood (CML) item parameter estimation of both sequential and cumulative deterministic multistage designs (Zwitser & Maris, 2015, <doi:10.1007/s11336-013-9369-6>) and probabilistic sequential and cumulative multistage designs (Steinfeld & Robitzsch, 2024, <doi:10.1007/s41237-024-00228-3>). Supports CML item parameter estimation of conventional linear designs and additional functions for the likelihood ratio test (Andersen, 1973, <doi:10.1007/BF02291180>) as well as functions for simulating various types of multistage designs.

This package implements tic-tac-toe game to play on console, either with human or AI players. Various levels of AI players are trained through the Q-learning algorithm.

This package provides functions for random generation, density, cumulative distribution, quantile function, moments, and log-likelihood for a three-parameter generalized Lindley-Poisson mixture model.

Generate constrained Delaunay triangulation meshes for use with stochastic partial differential equation (SPDE) spatial models (Lindgren, Rue and Lindstroem 2011 <doi:10.1111/j.1467-9868.2011.00777.x>). Provides automatic mesh generation from point coordinates with boundary constraints, Ruppert refinement for mesh quality, finite element method (FEM) matrix assembly (mass, stiffness, projection), barrier models, spherical meshes via icosahedral subdivision, and metric graph meshes for network geometries. Built on the CDT header-only C++ library (Amirkhanov 2024 <https://github.com/artem-ogre/CDT>). Designed as the mesh backend for the tulpa Bayesian hierarchical modelling engine but usable standalone for any spatial triangulation task.

Operators and functions provided by base R sometimes lack some features found in other programming languages, such as the ability to concatenate strings using + or to repeat strings using *. This package aims at providing such functionality without breaking existing code, i.e., only statements, that would throw errors in pure base R are patched.

Enables all rstan functionality for a TMB model object, in particular MCMC sampling and chain visualization. Sampling can be performed with or without Laplace approximation for the random effects. This is demonstrated in Monnahan & Kristensen (2018) <DOI:10.1371/journal.pone.0197954>.

Routines for the analysis of nonlinear time series. This work is largely inspired by the TISEAN project, by Rainer Hegger, Holger Kantz and Thomas Schreiber: <http://www.mpipks-dresden.mpg.de/~tisean/>.

This package provides tools to deploy TensorFlow <https://www.tensorflow.org/> models across multiple services. Currently, it provides a local server for testing cloudml compatible services.

Equilibrium models are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. The teems package handles all aspects of running equilibrium models while facilitating transparent and reproducible workflows.

Visualizes the relationship between allele frequency and effect size in genetic association studies. The input is a data frame containing association results. The output is a plot with the effect size of risk variants in the Y axis, and the allele frequency spectrum in the X axis. Corte et al (2023) <doi:10.1101/2023.04.21.23288923>.

The goal of tidyheatmaps is to simplify the generation of publication-ready heatmaps from tidy data. By offering an interface to the powerful pheatmap package, it allows for the effortless creation of intricate heatmaps with minimal code.

Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

This package provides utility functions for plotting. Includes functions for color manipulation, plot customization, panel size control, data optimization for plots, and layout adjustments.

This package produces weighted cross-tabulation tables for one or more outcome variables across one or more breakdown variables, and exports them directly to Excel'. For each outcome-by-breakdown combination, the package creates a weighted percentage table and a corresponding unweighted count table, with transparent handling of missing values and light, readable formatting. Designed to support social survey analysis workflows that require large sets of consistent, publication-ready tables.

This package provides bindings to an R grammar for Tree-sitter', to be used alongside the treesitter package. Tree-sitter builds concrete syntax trees for source files of any language, and can efficiently update those syntax trees as the source file is edited.

Interface to the API for TreeBASE <http://treebase.org> from R. TreeBASE is a repository of user-submitted phylogenetic trees (of species, population, or genes) and the data used to create them.

Type hints are special comments within a function body indicating the intended nature of the function's arguments in terms of data types, dimensions and permitted values. The actual parameters with which the function is called are evaluated against these type hint comments at run-time.

Introduction of qenv S4 class, that facilitates code execution and reproducibility in teal applications.

Information on all of the TriMet stops in the Portland Metro Area. It includes information such as the longitude, latitude, cross street, and direction of the stop. TriMet has catalogued these stops, 6880 in total.