Markdown To Question & Test Interoperability,
2021
San Jose State University
Markdown To Question & Test Interoperability, Su Kim
Master's Projects
As the classroom setting shifted to a virtual one as a result of Covid-19, numerous software are readily available to accommodate for the change, including Canvas, the online course management system. Canvas has a core feature that allows teachers to generate and administer quizzes for students through their interface, but it does not fully utilize the potential with online exams. The first step to exploring this potential is this project, known as Markdown to Question & Test Interoperability (M2QTI). Based on the QTI specifications, this tool lets users to plan and write quizzes in Markdown format. Combined with Canvas’s ability …
Applying Simulated Annealing As An Intelligent Genetic Mutation Operator For Finding Most Probable Explanations On Bayesian Belief Networks,
2021
The American University in Cairo AUC
Applying Simulated Annealing As An Intelligent Genetic Mutation Operator For Finding Most Probable Explanations On Bayesian Belief Networks, Sahr Attia Afara
Archived Theses and Dissertations
No abstract provided.
News From The Bioconductor Project,
2021
University of Nebraska - Lincoln
News From The Bioconductor Project, Bioconductor Core Team
The R Journal
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.14 was released on 27 October, 2021. It is compatible with R 4.1.0 and consists of 2083 software packages, 408 experiment data packages, 904 up-to-date annotation packages, and 29 workflows.
Changes In R,
2021
Czech Technical University
Changes In R, Tomas Kalibera, Sebastian Meyer, Kurt Hornik, Gennadiy Starostin, Luke Tierney
The R Journal
We present important changes in the development version of R (referred to as R-devel, to become R 4.2) and give a summary of the new search engine interfaced by RSiteSearch(). Some statistics on bug tracking activities in 2021 are also provided.
Rpese: Risk And Performance Estimators Standard Errors With Serially Dependent Data,
2021
University of British Columbia
Rpese: Risk And Performance Estimators Standard Errors With Serially Dependent Data, Anthony-Alexander Christidis, R Douglas Martin
The R Journal
The R package RPESE (Risk and Performance Estimators Standard Errors) implements a new method for computing accurate standard errors of risk and performance estimators when returns are serially dependent. The new method makes use of the representation of a risk or performance estimator as a summation of a time series of influence-function (IF) transformed returns, and computes estimator standard errors using a sophisticated method of estimating the spectral density at frequency zero of the time series of IF-transformed returns. Two additional packages used by RPESE are introduced, namely RPEIF which computes and provides graphical displays of the IF of risk …
The Vote Package: Single Transferable Vote And Other Electoral Systems In R,
2021
University of Washington
The Vote Package: Single Transferable Vote And Other Electoral Systems In R, Adrian E. Raftery, Hana ŠevčÍková, Bernard W. Silverman
The R Journal
We describe the vote package in R, which implements the plurality (or first-past-the-post), two-round runoff, score, approval, and Single Transferable Vote (STV) electoral systems, as well as methods for selecting the Condorcet winner and loser. We emphasize the STV system, which we have found to work well in practice for multi-winner elections with small electorates, such as committee and council elections, and the selection of multiple job candidates. For single-winner elections, STV is also called Instant Runoff Voting (IRV), Ranked Choice Voting (RCV), or the alternative vote (AV) system. The package also implements the STV system with equal preferences, for …
Volume Approximation And Sampling For Convex Polytopes In R,
2021
National & Kapodistrian University of Athens
Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos
The R Journal
Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language
Bssm: Bayesian Inference Of Non-Linear And Non-Gaussian State Space Models In R,
2021
University of Jyväskylä
Bssm: Bayesian Inference Of Non-Linear And Non-Gaussian State Space Models In R, Jouni Helske, Matti Vihola
The R Journal
We present an R package bssm for Bayesian non-linear/non-Gaussian state space modeling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package also accommodates discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post-correction to eliminate any approximation bias. The package also implements a direct pseudo-marginal MCMC and a delayed acceptance pseudo-marginal MCMC using intermediate approximations. The package offers an easy-to-use interface to define models with linear-Gaussian state …
Openskies - Integration Of Aviation Data Into The R Ecosystem,
2021
Okinawa Institute of Science and Technology Graduate University
Openskies - Integration Of Aviation Data Into The R Ecosystem, Rafael Ayala, Daniel Ayala, Lara Sellés Vidal, David Ruiz
The R Journal
Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over publicly accessible radio channels. Furthermore, the OpenSky Network provides multiple public resources to access such air traffic data from a large network of ADS-B receivers. Here, we present openSkies, the first R package for processing public air traffic data. The package provides an interface to the OpenSky Network resources, standardized data structures to represent the different entities involved in air traffic data, and functionalities to analyze and visualize such …
Passed: Calculate Power And Sample Size For Two Sample Tests,
2021
University of Missouri
Passed: Calculate Power And Sample Size For Two Sample Tests, Jinpu Li, Ryan .. Knigge, Kaiyi Chen, Emily V. Leary
The R Journal
Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.
Automatic Time Series Forecasting With Ata Method In R: Ataforecasting Package,
2021
Dokuz Eylul University
Automatic Time Series Forecasting With Ata Method In R: Ataforecasting Package, Ali Sabri Taylan, Güçkan Yapar, Hanife Taylan Selamlar
The R Journal
Ata method is a new univariate time series forecasting method that provides innovative solutions to issues faced during the initialization and optimization stages of existing methods. The Ata method’s forecasting performance is superior to existing methods in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or deseasonalized time series, where the deseasonalization can be performed via any preferred decomposition method. The R package ATAforecasting was developed as a comprehensive toolkit for automatic time series forecasting. It focuses on modeling all types of time series components with any preferred Ata methods and handling seasonality patterns by …
A New Versatile Discrete Distribution,
2021
The University of Auckland
A New Versatile Discrete Distribution, Rolf Turner
The R Journal
This paper introduces a new flexible distribution for discrete data. Approximate moment estimators of the parameters of the distribution, to be used as starting values for numerical optimization procedures, are discussed. “Exact” moment estimation, effected via a numerical procedure, and maximum likelihood estimation, are considered. The quality of the results produced by these estimators is assessed via simulation experiments. Several examples are given of fitting instances of the new distribution to real and simulated data. It is noted that the new distribution is a member of the exponential family. Expressions for the gradient and Hessian of the log-likelihood of the …
Robustbf: An R Package For Robust Solution To The Behrens-Fisher Problem,
2021
Eskisehir Osmangazi University
Robustbf: An R Package For Robust Solution To The Behrens-Fisher Problem, Gamze Güven, ŞÜkrü Acıtaş, Hatice ŞAmkar, Birdal ŞEnoğLu
The R Journal
Welch’s two-sample t-test based on least squares (LS) estimators is generally used to test the equality of two normal means when the variances are not equal. However, this test loses its power when the underlying distribution is not normal. In this paper, two different tests are proposed to test the equality of two long-tailed symmetric (LTS) means under heterogeneous variances. Adaptive modified maximum likelihood (AMML) estimators are used in developing the proposed tests since they are highly efficient under LTS distribution. An R package called RobustBF is given to show the implementation of these tests. Simulated Type I error rates …
Volesti: Volume Approximation And Sampling For Convex Polytopes In R,
2021
National & Kapodistrian University of Athens
Volesti: Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos
The R Journal
Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language.
Passed: Calculate Power And Sample Size For Two Sample Tests,
2021
University of Missouri
Passed: Calculate Power And Sample Size For Two Sample Tests, University Of Missouri Li, Ryan P. Knigge, Kaiyi Chen, Emily V. Leary
The R Journal
Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.
Robust And Efficient Optimization Using A Marquardt-Levenberg Algorithm With R Package Marqlevalg,
2021
Bordeaux Population Health Research Center
Robust And Efficient Optimization Using A Marquardt-Levenberg Algorithm With R Package Marqlevalg, Viviane Philipps, Boris P. Hejblum, Mélanie Prague, Daniel Commenges, Cécile Proust-Lima
The R Journal
Implementations in R of classical general-purpose algorithms for local optimization generally have two major limitations which cause difficulties in applications to complex problems: too loose convergence criteria and too long calculation time. By relying on a Marquardt-Levenberg algorithm (MLA), a Newton-like method particularly robust for solving local optimization problems, we provide with marqLevAlg package an efficient and general-purpose local optimizer which (i) prevents convergence to saddle points by using a stringent convergence criterion based on the relative distance to minimum/maximum in addition to the stability of the parameters and of the objective function; and (ii) reduces the computation time in …
Emss: New Em-Type Algorithms For The Heckman Selection Model In R,
2021
Konkuk University
Emss: New Em-Type Algorithms For The Heckman Selection Model In R, Kexuan Yang, Sang Kyu Lee, Jun Zhao, Hyoung-Moon Kim
The R Journal
When investigators observe non-random samples from populations, sample selectivity problems may occur. The Heckman selection model is widely used to deal with selectivity problems. Based on the EM algorithm, Zhao et al. (2020) developed three algorithms, namely, ECM, ECM(NR), and ECME(NR), which also have the EM algorithm’s main advantages: stability and ease of implementation. This paper provides the implementation of these three new EM-type algorithms in the package EMSS and illustrates the usage of the package on several simulated and real data examples. The comparison between the maximum likelihood estimation method (MLE) and three new EM-type algorithms in robustness issues …
Bayessenmc: An R Package For Bayesian Sensitivity Analysis Of Misclassification,
2021
University of Minnesota Twin Cities
Bayessenmc: An R Package For Bayesian Sensitivity Analysis Of Misclassification, Jinhui Yang, Lifeng Lin, Haitao Chu
The R Journal
In case–control studies, the odds ratio is commonly used to summarize the association between a binary exposure and a dichotomous outcome. However, exposure misclassification frequently appears in case–control studies due to inaccurate data reporting, which can produce bias in measures of association. In this article, we implement a Bayesian sensitivity analysis of misclassification to provide a full posterior inference on the corrected odds ratio under both non-differential and differential misclassification. We present an R (R Core Team, 2018) package BayesSenMC, which provides user-friendly functions for its implementation. The usage is illustrated by a real data analysis on the association between …
Dad: An R Package For Visualisation, Classification And Discrimination Of Multivariate Groups Modelled By Their Densities,
2021
Université d’Angers
Dad: An R Package For Visualisation, Classification And Discrimination Of Multivariate Groups Modelled By Their Densities, Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard
The R Journal
Multidimensional scaling (MDS), hierarchical cluster analysis (HCA), and discriminant analysis (DA) are classical techniques which deal with data made of n individuals and p variables. When the individuals are divided into T groups, the R package dad associates with each group a multivariate probability density function and then carries out these techniques on the densities, which are estimated by the data under consideration. These techniques are based on distance measures between densities: chi-square, Hellinger, Jeffreys, Jensen-Shannon, and Lp for discrete densities, Hellinger , Jeffreys, L2 , and 2-Wasserstein for Gaussian densities, and L2 for numeric non-Gaussian densities …
Stratigrapher: Concepts For Litholog Generation In R,
2021
University of Liege
Stratigrapher: Concepts For Litholog Generation In R, Sébastien Wouters, Anne-Christine Da Silva, Frédéric Boulvain, Xavier Devleeschouwer
The R Journal
The StratigrapheR package proposes new concepts for the generation of lithological logs, or lithologs, in R. The generation of lithologs in a scripting environment opens new opportunities for the processing and analysis of stratified geological data. Among the new concepts presented: new plotting and data processing methodologies, new general R functions, and computer-oriented data conventions are provided. The package structure allows for these new concepts to be further improved, which can be done independently by any R user. The current limitations of the package are highlighted, along with the limitations in R for geological data processing, to help identify the …
