Computer Sciences Commons^™

Measurement Errors In R, Iñaki Ucar, Edzer Pebesma, Arturo Azcorra

The R Journal

This paper presents an R package to handle and represent measurements with errors in a very simple way. We briefly introduce the main concepts of metrology and propagation of uncertainty, and discuss related R packages. Building upon this, we introduce the errors package, which provides a class for associating uncertainty metadata, automated propagation and reporting. Working with errors enables transparent, lightweight, less error-prone handling and convenient representation of measurements with errors. Finally, we discuss the advantages, limitations and future work of computing with errors.

Spatial Uncertainty Propagation Analysis With The Spup R Package, Kasia Sawicka, Gerard B.M. Heuvelink, Dennis J.J. Walvoort

The R Journal

Many environmental and geographical models, such as those used in land degradation, agroecological and climate studies, make use of spatially distributed inputs that are known imperfectly. The R package spup provides functions for examining the uncertainty propagation from input data and model parameters onto model outputs via the environmental model. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. The package also accommodates spatial auto-correlation within a variable and cross-correlation between variables. The MC realizations may be …

The Utiml Package: Multi-Label Classification In R, Adriano Rivolli, Andre C.P.L.F. De Carvalho

The R Journal

Learning classification tasks in which each instance is associated with one or more labels are known as multi-label learning. The implementation of multi-label algorithms, performed by different researchers, have several specificities, like input/output format, different internal functions, distinct programming language, to mention just some of them. As a result, current machine learning tools include only a small subset of multi-label decomposition strategies. The utiml package is a framework for the application of classification algorithms to multi-label data. Like the well known MULAN used with Weka, it provides a set of multi-label procedures such as sampling methods, transformation strategies, threshold functions, …

Nsroc: An R Package For Non-Standard Roc Curve Analysis, Sonia Pérez-Fernández, Pablo Martínez-Camblor, Peter Filzmoser, Norberto Corral

The R Journal

The receiver operating characteristic (ROC) curve is a graphical method which has become standard in the analysis of diagnostic markers, that is, in the study of the classification ability of a numerical variable. Most of the commercial statistical software provide routines for the standard ROC curve analysis. Of course, there are also many R packages dealing with the ROC estimation as well as other related problems. In this work we introduce the nsROC package which incorporates some new ROC curve procedures. Particularly: ROC curve comparison based on general distances among functions for both paired and unpaired designs; efficient confidence bands …

Stilt: Easy Emulation Of Time Series Ar(1) Computer Model Output In Multidimensional Parameter Space, Roman Olson, Kelsey L. Ruckert, Won Chang, Klaus Keller, Murali Haran, Soon-Il An

The R Journal

Statistically approximating or “emulating” time series model output in parameter space is a common problem in climate science and other fields. There are many packages for spatio-temporal modeling. However, they often lack focus on time series, and exhibit statistical complexity. Here, we present the R package stilt designed for simplified AR(1) time series Gaussian process emulation, and provide examples relevant to climate modelling. Notably absent is Markov chain Monte Carlo estimation – a challenging concept to many scientists. We keep the number of user choices to a minimum. Hence, the package can be useful pedagogically, while still applicable to real …

R Foundation News, Torsten Hothorn

The R Journal

Donations and members

Donations

Supporting benefactors

Supporting institutions

Supporting members

Sarima Analysis And Automated Model Reports With Bets, An R Package, Talitha F. Speranza, Pedro C. Ferreira, Jonatha A. Da Costa

The R Journal

This article aims to demonstrate how the powerful features of the R package BETS can be applied to SARIMA time series analysis. BETS provides not only thousands of Brazilian economic time series from different institutions, but also a range of analytical tools, and educational resources. In particular, BETS is capable of generating automated model reports for any given time series. These reports rely on a single function call and are able to build three types of models (SARIMA being one of them). The functions need few inputs and output rich content. The output varies according to the inputs and usually …

Profile Likelihood Estimation Of The Correlation Coefficient In The Presence Of Left, Right Or Interval Censoring And Missing Data, Yanming Li, Brenda W. Gillespie, Kerby Shedden, John A. Gillespie

The R Journal

We discuss implementation of a profile likelihood method for estimating a Pearson correlation coefficient from bivariate data with censoring and/or missing values. The method is implemented in an R package clikcorr which calculates maximum likelihood estimates of the correlation coefficient when the data are modeled with either a Gaussian or a Student t-distribution, in the presence of left, right, or interval censored and/or missing data. The R package includes functions for conducting inference and also provides graphical functions for visualizing the censored data scatter plot and profile log likelihood function. The performance of clikcorr in a variety of circumstances is …

Dot-Pipe: An S3 Extensible Pipe For R, John Mount, Nina Zumel

The R Journal

Pipe notation is popular with a large league of R users, with magrittr being the dominant realization. However, this should not be enough to consider piping in R as a settled topic that is not subject to further discussion, experimentation, or possibility for improvement. To promote innovation opportunities, we describe the wrapr R package and “dot-pipe” notation, a well behaved sequencing operator with S3 extensibility. We include a number of examples of using this pipe to interact with and extend other R packages.

Clustmixtype: User-Friendly Clustering Of Mixed-Type Data In R, Gero Szepannek

The R Journal

Clustering algorithms are designed to identify groups in data where the traditional emphasis has been on numeric data. In consequence, many existing algorithms are devoted to this kind of data even though a combination of numeric and categorical data is more common in most business applications. Recently, new algorithms for clustering mixed-type data have been proposed based on Huang’s k-prototypes algorithm. This paper describes the R package clustMixType which provides an implementation of k-prototypes in R.

Editorial, John Verzani

The R Journal

On behalf of the editorial board, I am pleased to present Volume 10, Issue 2 of the R Journal.

This issue covers a wide range of topics through its 37 articles. As is typical, many of these are related to packages that provide tools for new statistical modeling in R. Examples in this issue include "clustMixType: User-Friendly Clustering of Mixed-Type Data in R" by Szepannek and "BNSP: an R Package for Fitting Bayesian Semiparametric Regression Models and Variable Selection" by Papageorgiou.

Downside Risk Evaluation With The R Package Gas, David Ardia, Kris Boudt, Leopoldo Catania

The R Journal

Financial risk managers routinely use non–linear time series models to predict the downside risk of the capital under management. They also need to evaluate the adequacy of their model using so–called backtesting procedures. The latter involve hypothesis testing and evaluation of loss functions. This paper shows how the R package GAS can be used for both the dynamic prediction and the evaluation of downside risk. Emphasis is given to the two key financial downside risk measures: Value-at-Risk (VaR) and Expected Shortfall (ES). High-level functions for: (i) prediction, (ii) backtesting, and (iii) model comparison are discussed, and code examples are provided. …

Explanations Of Model Predictions With Live And Breakdown Packages, Mateusz Staniak, Przemysław Biecek

The R Journal

Complex models are commonly used in predictive modeling. In this paper we present R packages that can be used for explaining predictions from complex black box models and attributing parts of these predictions to input features. We introduce two new approaches and corresponding packages for such attribution, namely live and breakDown. We also compare their results with existing implementations of state-of-the-art solutions, namely, lime (Pedersen and Benesty, 2018) which implements Locally Interpretable Model-agnostic Explanations and iml (Molnar et al., 2018) which implements Shapley values.

Sdpt3r: Semidefinite Quadratic Linear Programming In R, Adam Rahman

The R Journal

We present the package sdpt3r, an R implementation of the Matlab package SDPT3 (Toh et al., 1999). The purpose of the software is to solve semidefinite quadratic linear programming (SQLP) problems, which encompasses problems such as D-optimal experimental design, the nearest correlation matrix problem, and distance weighted discrimination, as well as problems in graph theory such as finding the maximum cut or Lovasz number of a graph.

Current optimization packages in R include Rdsdp, Rcsdp, scs, cccp, and Rmosek. Of these, scs and Rmosek solve a similar suite of problems. In addition to these …

Geospatial Point Density, Paul F. Evangelista, David Beskow

The R Journal

This paper introduces a spatial point density algorithm designed to be explainable, meaning ful, and efficient. Originally designed for military applications, this technique applies to any spatial point process where there is a desire to clearly understand the measurement of density and maintain fidelity of the point locations. Typical spatial density plotting algorithms, such as kernel density estimation, implement some type of smoothing function that often results in a density value that is difficult to interpret. The purpose of the visualization method in this paper is to understand spatial point activity density with precision and meaning. The temporal tendency of …

Lmridge: A Comprehensive R Package For Ridge Regression, Muhammad Imdad Ullah, Bahauddin Zakariya University Aslam, Saima Atlaf

The R Journal

The ridge regression estimator, one of the commonly used alternatives to the conventional ordinary least squares estimator, avoids the adverse effects in the situations when there exists some considerable degree of multicollinearity among the regressors. There are many software packages available for estimation of ridge regression coefficients. However, most of them display limited methods to estimate the ridge biasing parameters without testing procedures. Our developed package, lmridge can be used to estimate ridge coefficients considering a range of different existing biasing parameters, to test these coefficients with more than 25 ridge related statistics, and to present different graphical displays of …

Scale-Out Algorithm For Apache Storm In Saas Environment, Ravi Kiran Puttaswamy

School of Computing: Dissertations, Theses, and Student Research

The main appeal of the Cloud is in its cost effective and flexible access to computing power. Apache Storm is a data processing framework used to process streaming data. In our work we explore the possibility of offering Apache Storm as a software service. Further, we take advantage of the cgroups feature in Storm to divide the computing power of worker machine into smaller units to be offered to users. We predict that the compute bounds placed on the cgroups could be used to approximate the state of the workflow. We discuss the limitations of the current schedulers in facilitating …

Reducing The Tail Latency Of A Distributed Nosql Database, Jun Wu

School of Computing: Dissertations, Theses, and Student Research

The request latency is an important performance metric of a distributed database, such as the popular Apache Cassandra, because of its direct impact on the user experience. Specifically, the latency of a read or write request is defined as the total time interval from the instant when a user makes the request to the instant when the user receives the request, and it involves not only the actual read or write time at a specific database node, but also various types of latency introduced by the distributed mechanism of the database. Most of the current work focuses only on reducing …

Deploying, Improving And Evaluating Edge Bundling Methods For Visualizing Large Graphs, Jieting Wu

School of Computing: Dissertations, Theses, and Student Research

A tremendous increase in the scale of graphs has been witnessed in a wide range of fields, which demands efficient and effective visualization techniques to assist users in better understandings of large graphs. Conventional node-link diagrams are often used to visualize graphs, whereas excessive edge crossings can easily incur severe visual clutter in the node-link diagram of a large graph. Edge bundling can effectively remedy visual clutter and reveal high-level graph structures. Although significant efforts have been devoted to developing edge bundling, three challenging problems remain. First, edge bundling techniques are often computationally expensive and are not easy to deploy …

Evoalloy: An Evolutionary Approach For Analyzing Alloy Specifications, Jianghao Wang

School of Computing: Dissertations, Theses, and Student Research

Using mathematical notations and logical reasoning, formal methods precisely define a program’s specifications, from which we can instantiate valid instances of a system. With these techniques, we can perform a variety of analysis tasks to verify system dependability and rigorously prove the correctness of system properties. While there exist well-designed automated verification tools including ones considered lightweight, they still lack a strong adoption in practice. The essence of the problem is that when applied to large real world applications, they are not scalable and applicable due to the expense of thorough verification process. In this thesis, I present a new …

Controller Evolution And Divergence: A Software Perspective, Balaji Balasubramaniam

School of Computing: Dissertations, Theses, and Student Research

Successful controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software.

In this thesis, we perform a first-of-its-kind study on the evolution of two popular open-source safety-critical autopilot control software -- ArduPilot, and Paparazzi, to better …

Supporting Diverse Customers And Prioritized Traffic In Next-Generation Passive Optical Networks, Naureen Hoque

School of Computing: Dissertations, Theses, and Student Research

The already high demand for more bandwidth usage has been growing rapidly. Access network traffic is usually bursty in nature and the present traffic trend is mostly video-dominant. This motivates the need for higher transmission rates in the system. At the same time, the deployment costs and maintenance expenditures have to be reasonable. Therefore, Passive Optical Networks (PON) are considered promising next-generation access technologies. As the existing PON standards are not suitable to support future-PON services and applications, the FSAN (Full Service Access Network) group and the ITU-T (Telecommunication Standardization Sector of the International Telecommunication Union) have worked on developing …

A Comprehensive Framework To Replicate Process-Level Concurrency Faults, Supat Rattanasuksun

School of Computing: Dissertations, Theses, and Student Research

Concurrency faults are one of the most damaging types of faults that can affect the dependability of today’s computer systems. Currently, concurrency faults such as process-level races, order violations, and atomicity violations represent the largest class of faults that has been reported to various Linux bug repositories. Clearly, existing approaches for testing such faults during software development processes are not adequate as these faults escape in-house testing efforts and are discovered during deployment and must be debugged.

The main reason concurrency faults are hard to test is because the conditions that allow these to occur can be difficult to replicate, …

Optical Wireless Data Center Networks, Abdelbaset S. Hamza

School of Computing: Dissertations, Theses, and Student Research

Bandwidth and computation-intensive Big Data applications in disciplines like social media, bio- and nano-informatics, Internet-of-Things (IoT), and real-time analytics, are pushing existing access and core (backbone) networks as well as Data Center Networks (DCNs) to their limits. Next generation DCNs must support continuously increasing network traffic while satisfying minimum performance requirements of latency, reliability, flexibility and scalability. Therefore, a larger number of cables (i.e., copper-cables and fiber optics) may be required in conventional wired DCNs. In addition to limiting the possible topologies, large number of cables may result into design and development problems related to wire ducting and maintenance, heat …

Amino Acid Pop-Set: Model File Name: Amino-Acid-Wgrp-Pop_Sc3.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model for protein primary structure. It consists of four amino acids (tryptophan, proline, arginine, and glycine) depicted in stick and space-fill representations, five peptide bonds depicted in space-fill, and an N-terminus and a C-terminus depicted in space-fill. It is designed so that students can make various peptides to explore the amount of space of the electron clouds of the amino acids and bonds, and explore the psi and phi angles for the peptides. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Amino acid pop-set”. This model has …

Lipoprotein Signal Peptidase Ii: Model File Name: 5dir-Lipoii-Reps_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of lipoprotein signal peptidase II (PDB: 5DIR). It is designed with different regions of the protein depicted in space-filling, ribbon, stick, and backbone-only representations to explore protein secondary structure and illustrate how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Lipoprotein signal peptidase II” and is intended to accompany the “Crambin”, “Cytochrome c” and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in …

3 Water Molecules: Model File Name: 3hoh-Final.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of 3 water molecules depicted in space-fill. It is designed to the same scale as the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models to illustrate the amount of space taken up by proteins. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “3 water molecules” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “Cytochrome c” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering …

Crambin: Model File Name: 2fd7-Crambin-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 2FD7). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Crambin” and is intended to accompany the “Lipoprotein signal peptidase II”, “Cytochrome c”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Cytochrome C: Model File Name: 1b7v-Cytc-Stick_Sc1-5.Stl, Michelle Howell, Rebecca Roston

3-D Printed Model Structural Files

This is a teaching model of cytochrome c (PDB: 1B7V). It is designed in a stick representation to explore protein secondary structure and how much space the protein takes up. The printable model is already uploaded to Shapeways.com in the MacroMolecules shop under the name “Cytochrome c” and is intended to accompany the “Lipoprotein signal peptidase II”, “Crambin”, and “3 water molecules” models. This model has been printed successfully using these parameters on Shapeways’ laser sintering printer in the following material: Processed Versatile Plastic (Strong & Flexible Plastic).

Girls Who Code 3rd-5th, Khristina Polivanov

Honors Program: Expanded Learning Clubs

The goal of the club is to encourage girls to be confident in themselves and their abilities while teaching them basic concepts used in computer science.