Three semi-parametric methods for detection of outliers in environmental data based on kernel regression and subsequent analysis of smoothing residuals. The first method (Campulova, Michalek, Mikuska and Bokal (2018) <DOI: 10.1002/cem.2997>) analyzes the residuals using changepoint analysis, the second method is based on control charts (Campulova, Veselik and Michalek (2017) <DOI: 10.1016/j.apr.2017.01.004>) and the third method (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>) analyzes the residuals using extreme value theory (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>).

This package provides tools for simulating draws from continuous time processes with well-defined exponential family random graph (ERGM) equilibria, i.e. ERGM generating processes (EGPs). A number of EGPs are supported, including the families identified in Butts (2023) <doi:10.1080/0022250X.2023.2180001>, as are functions for hazard calculation and timing calibration.

Fits a variety of hidden Markov models, structured in an extended generalized linear model framework. See T. Rolf Turner, Murray A. Cameron, and Peter J. Thomson (1998) <doi:10.2307/3315677>, and Rolf Turner (2008) <doi:10.1016/j.csda.2008.01.029> and the references cited therein.

Empirical likelihood (EL) inference for two-sample problems. The following statistics are included: the difference of two-sample means, smooth Huber estimators, quantile (qdiff) and cumulative distribution functions (ddiff), probability-probability (P-P) and quantile-quantile (Q-Q) plots as well as receiver operating characteristic (ROC) curves. EL calculations are based on J. Valeinis, E. Cers (2011) <http://home.lu.lv/~valeinis/lv/petnieciba/EL_TwoSample_2011.pdf>.

Simulation of Electric Vehicles charging sessions using Gaussian models, together with time-series power demand calculations.

Allows R users to retrieve and parse data from the Urban Institute's Education Data API <https://educationdata.urban.org/> into a data.frame for analysis.

Fits the space-time Epidemic Type Aftershock Sequence ('ETAS') model to earthquake catalogs using a stochastic declustering approach. The ETAS model is a spatio-temporal marked point process model and a special case of the Hawkes process. The package is based on a Fortran program by Jiancang Zhuang (available at <https://bemlar.ism.ac.jp/zhuang/software.html>), which is modified and translated into C++ and C such that it can be called from R. Parallel computing with OpenMP is possible on supported platforms.

This package provides functions for estimating EMP (Expected Maximum Profit Measure) in Credit Risk Scoring and Customer Churn Prediction, according to Verbraken et al (2013, 2014) <DOI:10.1109/TKDE.2012.50>, <DOI:10.1016/j.ejor.2014.04.001>.

Easily load and install multiple packages from different sources, including CRAN and GitHub. The libraries function allows you to load or attach multiple packages in the same function call. The packages function will load one or more packages, and install any packages that are not installed on your system (after prompting you). Also included is a from_import function that allows you to import specific functions from a package into the global environment.

This package provides methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, including the continual reassessment method (CRM) by O'Quigley et al. (1990) <doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3 described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended dose, stopping when a toxicity condition is met, or demanding that n patients are treated before stopping is allowed. By daisy-chaining together these classes using the pipe operator from magrittr', it is simple to tailor the behaviour of a dose-finding design so it behaves how the trialist wants. Having provided a flexible interface for specifying designs, we then provide functions to run simulations and calculate dose-paths for future cohorts of patients.

This package provides a light, simple tool for sending emails with minimal dependencies.

This package provides tools to analyze the embryo growth and the sexualisation thermal reaction norms. See <doi:10.7717/peerj.8451> for tsd functions; see <doi:10.1016/j.jtherbio.2014.08.005> for thermal reaction norm of embryo growth.

Use emailjs API easily in R'. This package is not official. <https://www.emailjs.com/docs/rest-api/send/>. You can send e-mail with emailjs with function, based on httr'. You can also make a shiny ui and server function. It can be used for making feedback form, inquiry, and so on.

This package provides a flexible framework for calculating Elo ratings and resulting rankings of any two-team-per-matchup system (chess, sports leagues, Go', etc.). This implementation is capable of evaluating a variety of matchups, Elo rating updates, and win probabilities, all based on the basic Elo rating system. It also includes methods to benchmark performance, including logistic regression and Markov chain models.

This package contains two functions that are intended to make tuning supervised learning methods easy. The eztune function uses a genetic algorithm or Hooke-Jeeves optimizer to find the best set of tuning parameters. The user can choose the optimizer, the learning method, and if optimization will be based on accuracy obtained through validation error, cross validation, or resubstitution. The function eztune.cv will compute a cross validated error rate. The purpose of eztune_cv is to provide a cross validated accuracy or MSE when resubstitution or validation data are used for optimization because error measures from both approaches can be misleading.

Easily export R graphs and statistical output to Microsoft Office / LibreOffice', Latex and HTML Documents, using sensible defaults that result in publication-quality output with simple, straightforward commands. Output to Microsoft Office is in editable DrawingML vector format for graphs, and can use corporate template documents for styling. This enables the production of standardized reports and also allows for manual tidy-up of the layout of R graphs in Powerpoint before final publication. Export of graphs is flexible, and functions enable the currently showing R graph or the currently showing R stats object to be exported, but also allow the graphical or tabular output to be passed as objects. The package relies on package officer for export to Office documents,and output files are also fully compatible with LibreOffice'. Base R', ggplot2 and lattice plots are supported, as well as a wide variety of R stats objects, via wrappers to xtable(), broom::tidy() and stargazer(), including aov(), lm(), glm(), lme(), glmnet() and coxph() as well as matrices and data frames and many more...

Interact with the FRED API, <https://fred.stlouisfed.org/docs/api/fred/>, to fetch observations across economic series; find information about different economic sources, releases, series, etc.; conduct searches by series name, attributes, or tags; and determine the latest updates. Includes functions for creating panels of related variables with minimal effort and datasets containing data sources, releases, and popular FRED tags.

R shiny web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package epiworldR (Meyer et al., 2023) <DOI:10.21105/joss.05781>. Some of the main features of the package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. epiworldRShiny provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.

The production of certified reference materials (CRMs) requires various statistical tests depending on the task and recorded data to ensure that reported values of CRMs are appropriate. Often these tests are performed according to the procedures described in ISO GUIDE 35:2017'. The eCerto package contains a Shiny app which provides functionality to load, process, report and backup data recorded during CRM production and facilitates following the recommended procedures. It is described in Lisec et al (2023) <doi:10.1007/s00216-023-05099-3> and can also be accessed online <https://apps.bam.de/shn00/eCerto/> without package installation.

Because fungicide resistance is an important phenotypic trait for fungi and oomycetes, it is necessary to have a standardized method of statistically analyzing the Effective Concentration (EC) values. This package is designed for those who are not terribly familiar with R to be able to analyze and plot an entire set of isolates using the drc package.

Use R to interface with the ETRADE API <https://developer.etrade.com/home>. Functions include authentication, trading, quote requests, account information, and option chains. A user will need an ETRADE brokerage account and ETRADE API approval. See README for authentication process and examples.

This package performs likelihood-based extreme value inferences with adjustment for the presence of missing values based on Simpson and Northrop (2026). A Generalised Extreme Value distribution is fitted to block maxima using maximum likelihood estimation, with the location and scale parameters reflecting the numbers of non-missing raw values in each block. A Bayesian version is also provided. For the purposes of comparison, there are options to make no adjustment for missing values or to discard any block maximum for which greater than a percentage of the underlying raw values are missing. Example datasets containing missing values are provided.

Parametric and nonparametric statistics for single-case design. Regarding nonparametric statistics, the index suggested by Parker, Vannest, Davis and Sauber (2011) <doi:10.1016/j.beth.2010.08.006> was included. It combines both nonoverlap and trend to estimate the effect size of a treatment in a single case design.

Gas/Liquid Chromatography-Mass Spectrometer(GC/LC-MS) Data Analysis for Environmental Science. This package covered topics such molecular isotope ratio, matrix effects and Short-Chain Chlorinated Paraffins analysis etc. in environmental analysis.