This package provides a client for the API of OpenDota. OpenDota is a web service which is provide DOTA2 real time data. Data is collected through the Steam WebAPI. With ROpenDota you can easily grab the latest DOTA2 statistics in R programming such as latest match on official international competition, analyzing your or enemy performance to learn their strategies,etc. Please see <https://github.com/rosdyana/ROpenDota> for more information.

Distance-sampling (<doi:10.1007/978-3-319-19219-2>) is a field survey and analytical method that estimates density and abundance of survey targets (e.g., animals) when detection probability declines with observation distance. Distance-sampling is popular in ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Analysis involves fitting smooth (parametric) curves to histograms of observation distances and using those functions to adjust density estimates for missed targets. Routines included here fit curves to observation distance histograms, estimate effective sampling area, density of targets in surveyed areas, and the abundance of targets in a surrounding study area. Confidence interval estimation uses built-in bootstrap resampling. Help files are extensive and have been vetted by multiple authors. Many tutorials are available on the package's website (URL below).

Bootstrap forecast densities for GARCH (Generalized Autoregressive Conditional Heteroskedastic) returns and volatilities using the robust residual-based bootstrap procedure of Trucios, Hotta and Ruiz (2017) <DOI:10.1080/00949655.2017.1359601>.

This package provides the hybrid Bayesian method Geometric Density Estimation. On the one hand, it scales the dimension of our data, on the other it performs inference. The method is fully described in the paper "Scalable Geometric Density Estimation" by Y. Wang, A. Canale, D. Dunson (2016) <http://proceedings.mlr.press/v51/wang16e.pdf>.

An R interface for libeemd (Luukko, Helske, Räsänen, 2016) <doi:10.1007/s00180-015-0603-9>, a C library of highly efficient parallelizable functions for performing the ensemble empirical mode decomposition (EEMD), its complete variant (CEEMDAN), the regular empirical mode decomposition (EMD), and bivariate EMD (BEMD). Due to the possible portability issues CRAN version no longer supports OpenMP, but you can install OpenMP-supported version from GitHub: <https://github.com/helske/Rlibeemd/>.

The GenDataSample() and GenDataPopulation() functions create, respectively, a sample or population of multivariate nonnormal data using methods described in Ruscio and Kaczetow (2008). Both of these functions call a FactorAnalysis() function to reproduce a correlation matrix. The EFACompData() function allows users to determine how many factors to retain in an exploratory factor analysis of an empirical data set using a method described in Ruscio and Roche (2012). The latter function uses populations of comparison data created by calling the GenDataPopulation() function. <DOI: 10.1080/00273170802285693>. <DOI: 10.1037/a0025697>.

Rcmdr interface to the sos package. The plug-in renders the sos searching functionality easily accessible via the Rcmdr menus. It also simplifies the task of performing multiple searches and subsequently obtaining the union or the intersection of the results.

Calculates tide heights based on tide station harmonics. It includes the harmonics data for 637 US stations. The harmonics data was converted from <https://github.com/poissonconsulting/rtide/blob/main/data-raw/harmonics-dwf-20151227-free.tar.bz2>, NOAA web site data processed by David Flater for XTide'. The code to calculate tide heights from the harmonics is based on XTide'.

The APT Package Management System provides Debian and Debian-derived Linux systems with a powerful system to resolve package dependencies. This package offers access directly from R. This can only work on a system with a suitable libapt-pkg-dev installation so functionality is curtailed if such a library is not found.

Infer log-linear Poisson Graphical Model with an auxiliary data set. Hot-deck multiple imputation method is used to improve the reliability of the inference with an auxiliary dataset. Standard log-linear Poisson graphical model can also be used for the inference and the Stability Approach for Regularization Selection (StARS) is implemented to drive the selection of the regularization parameter. The method is fully described in <doi:10.1093/bioinformatics/btx819>.

Interface for loading data from Google Ads API', see <https://developers.google.com/google-ads/api/docs/start>. Package provide function for authorization and loading reports.

Density discontinuity testing (a.k.a. manipulation testing) is commonly employed in regression discontinuity designs and other program evaluation settings to detect perfect self-selection (manipulation) around a cutoff where treatment/policy assignment changes. This package implements manipulation testing procedures using the local polynomial density estimators: rddensity() to construct test statistics and p-values given a prespecified cutoff, rdbwdensity() to perform data-driven bandwidth selection, and rdplotdensity() to construct density plots.

Discretize AR(1) process following Tauchen (1986) <http://www.sciencedirect.com/science/article/pii/0165176586901680>. A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued univariate Autoregressive process of first order is generated. It is a popular method used in economics and in finance.

Takes user-provided baseline data from groups of randomised controlled data and assesses whether the observed distribution of baseline p-values, numbers of participants in each group, or categorical variables are consistent with the expected distribution, as an aid to the assessment of integrity concerns in published randomised controlled trials. References (citations in PubMed format in details of each function): Bolland MJ, Avenell A, Gamble GD, Grey A. (2016) <doi:10.1212/WNL.0000000000003387>. Bolland MJ, Gamble GD, Avenell A, Grey A, Lumley T. (2019) <doi:10.1016/j.jclinepi.2019.05.006>. Bolland MJ, Gamble GD, Avenell A, Grey A. (2019) <doi:10.1016/j.jclinepi.2019.03.001>. Bolland MJ, Gamble GD, Grey A, Avenell A. (2020) <doi:10.1111/anae.15165>. Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2021) <doi:10.1016/j.jclinepi.2020.11.012>. Bolland MJ, Gamble GD, Avenell A, Grey A. (2021) <doi:10.1016/j.jclinepi.2021.05.002>. Bolland MJ, Gamble GD, Avenell A, Cooper DJ, Grey A. (2023) <doi:10.1016/j.jclinepi.2022.12.018>. Carlisle JB, Loadsman JA. (2017) <doi:10.1111/anae.13650>. Carlisle JB. (2017) <doi:10.1111/anae.13938>.

This package provides a research infrastructure to develop and evaluate collaborative filtering recommender algorithms. This includes a sparse representation for user-item matrices, many popular algorithms, top-N recommendations, and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.

This package provides functions to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker.

Allow access to both public and private end points to Coinbase Pro (erstwhile GDAX) cryptocurrency exchange. For authenticated flow, users must have valid api, secret and passphrase to be able to connect.

Create plots and LaTeX tables that look like SPSS output for use in teaching materials. Rather than copying-and-pasting SPSS output into documents, R code that mocks up SPSS output can be integrated directly into dynamic LaTeX documents with tools such as knitr. Functionality includes statistical techniques that are typically covered in introductory statistics classes: descriptive statistics, common hypothesis tests, ANOVA, and linear regression, as well as box plots, histograms, scatter plots, and line plots (including profile plots).

Robust (outlier-resistant) estimators of finite population characteristics like of means, totals, ratios, regression, etc. Available methods are M- and GM-estimators of regression, weight reduction, trimming, and winsorization. The package extends the survey <https://CRAN.R-project.org/package=survey> package.

This package contains three functions that access environmental data from any ERDDAPâ ¢ data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the rerddap package to extract the data, and should work with any ERDDAPâ ¢ server. There are also two functions, plotBBox() and plotTrack() that use the plotdap package to simplify the creation of maps of the data.

An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data as presented in Sarrias (2016) <doi:10.18637/jss.v074.i10>.

This package provides a direct interface to the underlying XML representation of DDI Codebook 2.5 with flexible API creation.

Processing and analysis of targeted sequencing data. The package provides a user-friendly interface for core VSEARCH (Rognes et al. (2016), <doi:10.7717/peerj.2584>) functions, in addition to tools for visualization and parameter tuning.

Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>. Publication: Kapsner et al. (2021) <doi:10.1002/ijc.33681>.