Programming Languages and Compilers Commons^™

On The Feasibility Of Detecting Cross-Platform Code Clones Via Identifier Similarity, Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

More and more mobile applications run on multiple mobile operating systems to attract more users of different platforms. Although versions on different platforms are implemented in different programming languages (e.g., Java and Objective-C), there must be many code snippets that implement the similar business logic on different platforms. Such code snippets are called cross-platform clones. It is challenging but essential to detect such clones for software maintenance. Due to the practice that developers usually use some common identifiers when implementing the same business logic on different platforms, in this paper, we investigate the identifier similarity of the same mobile application …

Effective Compiler Error Message Enhancement For Novice Programming Students, Brett Becker Dr, Graham Glanville

Faculty Research

Programming is an essential skill that all computing students must master. However programming can be difficult to learn. Compiler error messages are crucial for correcting errors, but are often difficult to understand and pose a barrier to progress for many novices. High frequencies of errors, particularly repeated errors, have been shown to be indicators of students who are struggling with learning to program. This study involves a custom IDE that enhances Java compiler error messages, intended to be more useful to novices than those supplied by the compiler. The effectiveness of this approach was tested in an empirical control/intervention study …

Decision Modeling And Empirical Analysis Of Mobile Financial Services, Jun Liu

Dissertations and Theses Collection

The past twenty years have been a time of many new technological developments, changing business practices, and interesting innovations in the financial information system (IS) and technology landscape. As the financial services industry has been undergoing the digital transformation, the emergence of mobile financial services has been changing the way that customers pay for goods and services purchases and interact with financial institutions. This dissertation seeks to understand the evolution of the mobile payments technology ecosystem and how firms make mobile payments investment decisions under uncertainty, as well as examines the influence of mobile banking on customer behavior and financial …

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.1 patched

CHANGES IN R 3.3.1

CHANGES IN R 3.3.0

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

In the past 8 months,1322 new packages were added to the CRAN package repository. 43 packages were unarchived,48 archived,1 package had to be removed.The following shows the growth of the number of active packages in the CRAN package repository:

Nonparametric Tests For The Interaction In Two-Way Factorial Designs Using R, Jos Feys

The R Journal

An increasing number of R packages include nonparametric tests for the interaction in two-way factorial designs. This paper briefly describes the different methods of testing and reports the resulting p-values of such tests on datasets for four types of designs: between, within, mixed, and pretest-posttest designs. Potential users are advised only to apply tests they are quite familiar with and not be guided by p-values for selecting packages and tests.

Using Decipher V2.0 To Analyze Big Biological Sequence Data In R, Erik S. Wright

The R Journal

In recent years, the cost of DNA sequencing has decreased at a rate that has outpaced improvements in memory capacity. It is now common to collect or have access to many gigabytes of biological sequences. This has created an urgent need for approaches that analyze sequences in subsets without requiring all of the sequences to be loaded into memory at one time. It has also opened opportunities to improve the organization and accessibility of information acquired in sequencing projects. The DECIPHER package offers solutions to these problems by assisting in the curation of large sets of biological sequences stored in …

Scmamp: Statistical Comparison Of Multiple Algorithms In Multiple Problems, Borja Calvo, Guzmán Santafé

The R Journal

Comparing the results obtained by two or more algorithms in a set of problems is a central task in areas such as machine learning or optimization. Drawing conclusions from these comparisons may require the use of statistical tools such as hypothesis testing. There are some interesting papers that cover this topic. In this manuscript we present scmamp, an R package aimed at being a tool that simplifies the whole process of analyzing the results obtained when comparing algorithms, from loading the data to the production of plots and tables.

Comparing the performance of different algorithms is an essential step …

Swmpr: An R Package For Retrieving, Organizing, And Analyzing Environmental Data For Estuaries, Marcus W. Beck

The R Journal

The System-Wide Monitoring Program (SWMP)was implemented in 1995 by the US National Estuarine Research Reserve System. This program has provided two decades of continuous monitoring data at over 140 fixed stations in 28 estuaries. However, the increasing quantity of data provided by the monitoring network has complicated broad-scale comparisons between systems and, in some cases, prevented simple trend analysis of water quality parameters at individual sites. This article describes the SWMPr package that provides several functions that facilitate data retrieval, organization, and analysis of time series data in the reserve estuaries. Previously unavailable functions for estuaries are also provided to …

Spatio-Temporal Interpolation Using Gstat, Benedikt Gräler, Edzer Pebesma, Gerard Heuvelink

The R Journal

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. Inareal-world application we comparespatio temporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the …

Model Builder For Item Factor Analysis With Openmx, Joshua N. Pritikin, Karen M. Schmidt

The R Journal

We introduce a shiny web application to facilitate the construction of Item Factor Analysis (a.k.a. Item Response Theory) models using the OpenMx package. The web application assists with importing data, outcome recoding, and model specification. However, the app does not conduct any analysis but, rather, generates an analysis script. Generated Rmarkdown output serves dual purposes: to analyze a data set and demonstrate good programming practices. The app can be used as a teaching tool or as a starting point for custom analysis scripts.

Quickpsy: An R Package To Fit Psychometric Functions For Multiple Groups, Daniel Linares, Joan López-Moliner

The R Journal

quickpsy is a package to parametrically fit psychometric functions. In comparison with previous R packages, quickpsy was built to easily fit and plot data for multiple groups. Here, we describe the standard parametric model used to fit psychometric functions and the standard estimation of its parameters using maximum likelihood. We also provide examples of usage of quickpsy, including how allowing the lapse rate to vary can sometimes eliminate the bias in parameter estimation, but not in general. Finally, we describe some implementation details, such as how to avoid the problems associated to round-off errors in the maximisation of the …

Variable Clustering In High-Dimensional Linear Regression: The R Package Clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, Mickael Canouil

The R Journal

Dimension reduction is one of the biggest challenges in high-dimensional regression models. We recently introduced a new methodology based on variable clustering as a means to reduce dimensionality. We present here the R package clere that implements some refinements of this methodology. An overview of the package functionalities as well as examples to run an analysis are described. Numerical experiments on real data were performed to illustrate the good predictive performance of our parsimonious method compared to standard dimension reduction approaches.

Maps, Coordinate Reference Systems And Visualising Geographic Data With Mapmisc, Patrick E. Brown

The R Journal

The mapmisc package provides functions for visualising geospatial data, including fetching background map layers, producing colour scales and legends, and adding scale bars and orientation arrows to plots. Background maps are returned in the coordinate reference system of the dataset supplied, and inset maps and direction arrows reflect the map projection being plotted. This is a “light weight” package having an emphasis on simplicity and ease of use

Editorial, Michael Lawrence

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 8, Issue 1 of the R Journal. This issue contains 27 contributed research articles. Each of them either presents an R package, a specific extension of an R package or applications using R packages available from the Comprehensive R Archive Network (CRAN, http:://CRAN.R-project.org). It thus provides a small but current cross-section of the burgeoning R ecosystem.

Metaplus: An R Package For The Analysis Of Robust Meta-Analysis And Meta-Regression, Ken J. Beath

The R Journal

The metaplus package is described with examples of its use for fitting meta-analysis and meta-regression. For either meta-analysis or meta-regression it is possible to fit one of three models: standard normal random effect, t-distribution random effect or mixture of normal random effects. The latter two models allow for robustness by allowing for a random effect distribution with heavier tails than the normal distribution, and for both robust models the presence of outliers may be tested using the parametric bootstrap. For the mixture of normal random effects model the outlier studies may be identified through their posterior probability of membership in …

Conditional Fractional Gaussian Fields With The Package Fieldsim, Alexandre Brouste, Jacques Istas, Sophie Lambert-Lacroix

The R Journal

We propose an effective and fast method to simulate multidimensional conditional fractional Gaussian fields with the package FieldSim. Our method is valid not only for conditional simulations associated to fractional Brownian fields, but to any Gaussian field and on any (non regular) grid of points.

Progenyclust: An R Package For Progeny Clustering, Chenyue W. Hu, Amina A. Qutub

The R Journal

Identifying the optimal number of clusters is a common problem faced by data scientists in various research fields and industry applications. Though many clustering evaluation techniques have been developed to solve this problem, the recently developed algorithm Progeny Clustering is a much faster alternative and one that is relevant to biomedical applications. In this paper, we introduce an R package progenyClust that implements and extends the original Progeny Clustering algorithm for evaluating clustering stability and identifying the optimal cluster number. We illustrate its applicability using two examples: a simulated test dataset for proof-of-concept, and a cell imaging dataset for demonstrating …

Statmod: Probability Calculations For The Inverse Gaussian Distribution, Göknur Giner, Gordon K. Smyth

The R Journal

The inverse Gaussian distribution (IGD) is a well known and often used probability distribution for which fully reliable numerical algorithms have not been available. We develop fast, reliable basic probability functions (dinvgauss, pinvgauss, qinvgauss and rinvgauss) for the IGD that work for all possible parameter values and which achieve close to full machine accuracy. The most challenging task is to compute quantiles for given cumulative probabilities and we develop a simple but elegant mathematical solution to this problem. We show that Newton’s method for finding the quantiles of a IGD always converges monotonically when started from the mode of the …

Heteroscedastic Censored And Truncated Regression With Crch, Jakob W. Messner, Georg J. Mayr, Achim Zeileis

The R Journal

The crch package provides functions for maximum likelihood estimation of censored or truncated regression models with conditional heteroscedasticity along with suitable standard methods to summarize the fitted models and compute predictions, residuals, etc. The supported distributions include left- or right-censored or truncated Gaussian, logistic, or student-t distributions with potentially different sets of regressors for modeling the conditional location and scale. The models and their R implementation are introduced and illustrated by numerical weather prediction tasks using precipitation data for Innsbruck (Austria).