Numerical Analysis and Scientific Computing Commons^™

Similar: R Code Clone And Plagiarism Detection, Maciej Bartoszuk, Marek Gagolewski

The R Journal

Third-party software for assuring source code quality is becoming increasingly popular. Tools that evaluate the coverage of unit tests, perform static code analysis, or inspect run-time memory use are crucial in the software development life cycle. More sophisticated methods allow for performing meta-analyses of large software repositories, e.g., to discover abstract topics they relate to or common design patterns applied by their developers. They may be useful in gaining a better understanding of the component interdependencies, avoiding cloned code as well as detecting plagiarism in programming classes.

Ameaningful measure of similarity of computer programs often forms the basis of such …

Coxphlb: An R Package For Analyzing Length Biased Data Under Cox Model, Chi Hyun Lee, Heng Zhou, Jing Ning, Diane D. Liu, Yu Shen

The R Journal

Data subject to length-biased sampling are frequently encountered in various applications including prevalent cohort studies and are considered as a special case of left-truncated data under the stationarity assumption. Many semiparametric regression methods have been proposed for length biased data to model the association between covariates and the survival outcome of interest. In this paper, we present a brief review of the statistical methodologies established for the analysis of length-biased data under the Cox model, which is the most commonly adopted semiparametric model, and introduce an R package CoxPhLb that implements these methods. Specifically, the package includes features such as …

The R Package Nonprobest For Estimation In Non-Probability Surveys, M. Rueda, R. Ferri-García, L. Castro

The R Journal

Different inference procedures are proposed in the literature to correct selection bias that might be introduced with non-random sampling mechanisms. The R package NonProbEst enables the estimation of parameters using some of these techniques to correct selection bias in non-probability surveys. The mean and the total of the target variable are estimated using Propensity Score Adjustment, calibration, statistical matching, model-based, model-assisted and model-calibratated techniques. Confidence intervals can also obtained for each method. Machine learning algorithms can be used for estimating the propensities or for predicting the unknown values of the target variable for the non-sampled units. Variance of a given …

Variable Importance Plots: An Introduction To The Vip Package, Brandon M. Bartoszuk, Marek Gagolewski

The R Journal

In the era of “big data”, it is becoming more of a challenge to not only build state-of-the-art predictive models, but also gain an understanding of what’s really going on in the data. For example, it is often of interest to know which, if any, of the predictors in a fitted model are relatively influential on the predicted outcome. Some modern algorithms—like random forests (RFs) and gradient boosted decision trees (GBMs)—have a natural way of quantifying the importance or relative influence of each feature. Other algorithms—like naive Bayes classifiers and support vector machines—are not capable of doing so and model-agnostic …

Tsmp: An R Package For Time Series With Matrix Profile, Francisco Bischoff, Pedro Pereira Rodriques

The R Journal

This article describes tsmp, an R package that implements the MP concept for TS. The tsmp package is a toolkit that allows all-pairs similarity joins, motif, discords and chains discovery, semantic segmentation, etc. Here we describe how the tsmp package may be used by showing some of the use-cases from the original articles and evaluate the algorithm speed in the R environment. This package can be downloaded at https://CRAN.R-project.org/package=tsmp.

R Foundation News, Torsten Hothorn

The R Journal

Membership fees and donations received between 2020-02-24 and 2020-09-08.

Projectmanagement: An R Package For Managing Projects, Juan Carlos Gonçalves-Dosantos, Ignacio García-Jurado, Julián Costa

The R Journal

Project management is an important body of knowledge and practices that comprises the planning, organisation and control of resources to achieve one or more pre-determined objectives. In this paper, we introduce ProjectManagement, a new R package that provides the necessary tools to manage projects in a broad sense, and illustrate its use by examples.

Npordtests: An R Package Of Nonparametric Tests For Equality Of Location Against Ordered Alternatives, Bulent Altunkaynak, Hamza Gamgam

The R Journal

Ordered alternatives are an important statistical problem in many situation such as increased risk of congenital malformation caused by excessive alcohol consumption during pregnancy life test experiments, drug-screening studies, dose-finding studies, the dose-response studies, age-related response. There are numerous other examples of this nature. In this paper, we present the npordtests package to test the equality of locations for ordered alternatives. The package includes the Jonckheere Terpstra, Beier and Buning’s Adaptive, Modified Jonckheere-Terpstra, Terpstra-Magel, Ferdhiana Terpstra-Magel, KTP, S and Gaur’s Gc tests. A simulation study is conducted to determine which test is the most appropriate test for which scenario and …

Spinifex: An R Package For Creating A Manual Tour Of Low-Dimensional Projections Of Multivariate Data, Nicholas Spyrison, Dianne Cook

The R Journal

Dynamic low-dimensional linear projections of multivariate data collectively known as tours provide an important tool for exploring multivariate data and models. The R package tourr provides functions for several types of tours: grand, guided, little, local and frozen. Each of these can be viewed dynamically, or saved into a data object for animation. This paper describes a new package, spinifex, which provides a manual tour of multivariate data where the projection coefficient of a single variable is controlled. The variable is rotated fully into the projection, or completely out of the projection. The resulting sequence of projections can be …

Mistr: A Computational Framework For Mixture And Composite Distributions, Lukas Sablica, Kurt Hornik

The R Journal

No abstract provided.

Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis

The R Journal

In the past 8 months, 1554 new packages were added to the CRAN package repository. 96 packages were unarchived and 843 were archived. The following shows the growth of the number of active packages in the CRAN package repository:

Skew-T Expected Information Matrix Evaluation And Use For Standard Error Calculations, R. Douglas Martin, Chindhanai Uthaisaad, Daniel Z. Xia

The R Journal

Skew-t distributions derived from skew-normal distributions, as developed by Azzalini and several co-workers, are popular because of their theoretical foundation and the availability of computational methods in the R package sn. One difficulty with this skew-t family is that the elements of the expected information matrix do not have closed form analytic formulas. Thus, we developed a numerical integration method of computing the expected information matrix in the R package skewtInfo. The accuracy of our expected information matrix calculation method was confirmed by comparing the result with that obtained using an observed information matrix for a very large sample …

Tools For Analyzing R Code The Tidy Way, Lucy D'Agostino Mcgowan, Sean Kross, Jeffrey Leek

The R Journal

With the current emphasis on reproducibility and replicability, there is an increasing need to examine how data analyses are conducted. In order to analyze the between researcher variability in data analysis choices as well as the aspects within the data analysis pipeline that contribute to the variability in results, we have created two R packages: matahari and tidycode. These packages build on methods created for natural language processing; rather than allowing for the processing of natural language, we focus on R code as the substrate of interest. The matahari package facilitates the logging of everything that is typed in the …

Individual-Level Modelling Of Infectious Disease Data: Epiilm, Vineetha Warriyar, Waleed Almutiry, Rob Deardon

The R Journal

In this article we introduce the R package EpiILM, which provides tools for simulation from, and inference for, discrete-time individual-level models of infectious disease transmission proposed by Deardon et al. (2010). The inference is set in a Bayesian framework and is carried out via Metropolis Hastings Markov chain Monte Carlo (MCMC). For its fast implementation, key functions are coded in Fortran. Both spatial and contact network models are implemented in the package and can be set in either susceptible-infected (SI) or susceptible-infected-removed (SIR) compartmental frameworks. Use of the package is demonstrated through examples involving both simulated and real data.

Conference Report: Why R? 2019, Michał Burdukiewicz, Filip Pietluch, Jarosław Chilimoniuk, Katarzyna Sidorczuk, Dominik Rafacz, Leon Eyrich Jessen, Stefan Rödiger, Marcin Kosiński, Piotr Wójcik

The R Journal

WhyR?conferences have been the hallmark of the Why R? Foundation (whyr.pl). Our goal has been to establish a series of international R-related events in Poland. After three years, weare happy to announce that our main event, the Why R? conference, has become one of the largest annual R conferences in Central Europe.

Difnlr: Generalized Logistic Regression Models For Dif And Ddf Detection, Adéla Hladká, Patrícia Martinková

The R Journal

Differential item functioning (DIF) and differential distractor functioning (DDF) are impor tant topics in psychometrics, pointing to potential unfairness in items with respect to minorities or different social groups. Various methods have been proposed to detect these issues. The difNLR R package extends DIF methods currently provided in other packages by offering approaches based on generalized logistic regression models that account for possible guessing or inattention, and by pro viding methods to detect DIF and DDF among ordinal and nominal data. In the current paper, we describe implementation of the main functions of the difNLR package, from data generation, through …

Survboost: An R Package For High-Dimensional Variable Selection In The Stratified Proportional Hazards Model Via Gradient Boosting, Emily Morris, Kevin He, Yanming Li, Yi Li, Jian Kang

The R Journal

High-dimensional variable selection in the proportional hazards (PH) model has many successful applications in different areas. In practice, data may involve confounding variables that do not satisfy the PH assumption, in which case the stratified proportional hazards (SPH) model can be adopted to control the confounding effects by stratification without directly modeling the confounding effects. However, there is a lack of computationally efficient statistical software for high-dimensional variable selection in the SPH model. In this work an R package, SurvBoost, is developed to implement the gradient boosting algorithm for fitting the SPH model with high-dimensional covariate variables. Simulation studies …

Copulacenr: Copula Based Regression Models For Bivariate Censored Data In R, Tao Sun, Ying Ding

The R Journal

Bivariate time-to-event data frequently arise in research areas such as clinical trials and epidemiological studies, where the occurrence of two events are correlated. In many cases, the exact event times are unknown due to censoring. The copula model is a popular approach for modeling correlated bivariate censored data, in which the two marginal distributions and the between margin dependence are modeled separately. This article presents the R package CopulaCenR, which is designed for modeling and testing bivariate data under right or (general) interval censoring in a regression setting. It provides a variety of Archimedean copula functions including a flexible two-parameter …

Sortedeffects: Sorted Causal Effects In R, Schuowen Chen, Victor Chernozhukov, Iván Fernández-Val, Ye Luo

The R Journal

Chernozhukov et al. (2018) proposed the sorted effect method for nonlinear regression models. This method consists of reporting percentiles of the partial effects, the sorted effects, in addition to the average effect commonly used to summarize the heterogeneity in the partial effects. They also propose to use the sorted effects to carry out classification analysis where the observational units are classified as most and least affected if their partial effect are above or below some tail sorted effects. The R package SortedEffects implements the estimation and inference methods therein and provides tools to visualize the results. This vignette serves as …

Realistic Real-Time Road Rendering Technology Based On Road Boundaryalpha-Map, Jinlian Du, Shang Xin, Fengchao Zhao

Journal of System Simulation

Abstract: A method of realistic real-time rendering based on road boundary alpha-map was proposed to eliminate the blur and aliasing issues produced by traditional rendering method based on buffer mechanism. In the method, the road was generated by buffer mechanism based on grid model of terrain, and the road's borders were constructed by analyzing the characteristics of road boundary grids. Based on these, three types of road boundary alpha-maps were designed for producing the road borders with realistic visual effects. Experiment shows that the method can improve the rendering realism of the road borders than traditional method. Another advantage of …

Survey Of Studies On Numerical Simulations Of Optical-Wave Propagation In Atmospheric Turbulence, Bin Ren, Chunyi Chen, Huamin Yang

Journal of System Simulation

Abstract: The complicated random behavior of atmospheric turbulence makes it difficult to verify the theories of optical-wave propagation in atmospheric turbulence by conducting experimental measurements. The parameters used in numerical simulations can be easily controlled; therefore numerical simulations have been used as another important tool to investigate the optical-wave propagation in atmospheric turbulence. Based on the existing literature, both the theoretical models and numerical generating methods for random phase screens of atmospheric turbulence are surveyed, and the spatial sampling constraints for numerical simulations of optical propagation in atmospheric turbulence were summarized. By comprehending the existing results, it has been pointed …

A Way Of Integrated Navigation Fault Detection Of Near Space Hypersonic Cruising Aircraft, Hailin Li, Bin Zhang, Dewei Wu, Lu Hu

Journal of System Simulation

Abstract: The doppler shift is augmented, that causes acquisition and tracking of GNSS losing, error of CNS's ray propagation also causes the problem of celestial body tracking when aircraft is hypersonically flighting. A way of INS/GNSS/CNS integrated navigation fault detection of the hypersonic cruising aircraft based on the residual chi-square-Fuzzy ARTMAP (Adaptive Resonance Theory Map) fast neural networks was proposed. The fault diagnostic elements of INS/GNSS/CNS integrated navigation system of the hypersonic cruising aircraft were given; the detection function formula of residual chi-square test and Fuzzy ARTMAP fast neural networks arithmetic was deduced; the realizing way was studied. The …

Simulation Analysis On Ballistic Deflection Of Projectile Obliquely Penetrating Into Concrete, Jianfeng Xue, Peihui Shen, Xiaoming Wang

Journal of System Simulation

Abstract: In order to study the trajectory deflection law of projectiles obliquely penetrating into concrete targets, based on the theory of rigid body kinematics and cavity expansion, the penetration motion differential equations of ogive-nosed projectile were established. The variation rules of trajectory offset and invasion depth were given in different initial conditions through the programming calculation and numerical simulation by MATALB and ANSYS-LYNA software. The calculation results agree well with experimental data. The results show that the influence of penetration depth and deflection angle increase with the oblique angle increasing. The influence of ballistic deflection decreases with the …

Multi-Rate Simulation Based On Explicit-Implicit Hybrid Integration, Bingda Zhang, Chen Ming, Wang Xiao, Lanyu Wang

Journal of System Simulation

Abstract: A multi-rate simulation method based on explicit-implicit hybrid integration algorithm for the grid-connected photovoltaic system which included power electronic devices with a variety of switching frequency was put forward. Inductances and capacitances were used to divide the grid-connected photovoltaic system into subsystems. A multi-rate interface was put forward to satisfy the request of real time. The stability criterion of the multi-rate simulation algorithm was put forward. FPGA was used as a platform to build the digital grid-connected photovoltaic system. The hardware in loop test for DC/DC and DC/AC converter controllers was conducted on this platform to verify the accuracy …

Reachable Set Modeling Approach For Autonomous Vehicle's Dynamic Conflict Control, Cao Kai, Xiufang Liu, Yang Xu, Shen Peng

Journal of System Simulation

Abstract: Aiming at the problem of active safety control modeling for autonomous vehicles, a combined method using the formal modeling and the dynamic non-cooperative game theory was proposed for discussing a control strategy of trajectory tracking and collision avoidance under dynamic conflict condition between autonomous vehicles. And it was proposed to divide the system control into three modes: trajectory tracking, collision avoidance and switching between trajectory tracking and collision avoidance. Taking into account the complexity as a hybrid systems and the existence of the trajectory tracking error for autonomous vehicle, a modeling approach based on reachable set was proposed for …

Fast Tree Modeling Method Based On Simple Freehand Sketch, Ma Ling, Xiaoping Liu, Xiaoping Liu

Journal of System Simulation

Abstract: Aiming at problems such as complicated process and professional knowledge requirements in tree modeling, a quick tree modeling method for non-experts was proposed, combining branch library with simple sketch to make non-experts create tree model quickly. The method preprocessed the sketch to eliminate noise and error points and identify the strokes, the trunk and branch were reconstructed, child three-dimensional profile was built through the two-dimensional canopy profile, under the constraint of the child profile, suitable branches from library and insert were extracted into the branches, consequently the whole tree model was completed. Experimental results show that this method …

Weighted Online Estimation Of Soc Based On Adaptive Battery Model, Haohao Sun, Tinglong Pan, Dinghui Wu

Journal of System Simulation

Abstract: Aiming at the problem that the traditional lithium battery model has poor adaptive ability in SOC estimation and the local estimation accuracy of the single SOC estimation algorithm is low, online identification of model parameters with Multi-Innovation Stochastic Gradient algorithm and method of weighted online estimation of SOC was proposed. The results of lithium-ion battery model parameters online identification updated in real time, realizing lithium-ion battery model adaptive. Aiming at the estimation of SOC, a method of weighted online estimation method based on the PI (proportion and integral) regulator's OCV combined with Ah (an integral method) was proposed. Weights …

Performance Modeling Of Cryptographic Service System Virtualization Based On Issm, Songhui Guo, Qingbao Li, Sun Lei, Xuerong Gong, Tianchi Yang

Journal of System Simulation

Abstract: The complicated architecture of cryptographic service system virtualization raised the difficulty of performance modeling. A performance modeling approach based on ISSMs was proposed. The approach divided the execution process into two stages, host preprocessing and arithmetic-module calculating, and built two sub-models based on queuing theory. On this basis, the effectiveness of this approach was verified. The results show that this method can analyze the impacts on system performance caused by task arrival rates, host and cryptographic card configurations quantitatively, and also be helpful for providing reasonable solutions to deploy virtualized cryptographic service system on cloud computing platforms.

Multi-Variable Modeling Research For Main-Steam Temperature Of Power Station Boiler Based On Improved Differential Evolution Algorithm, Li Qin, Zhang Hao, Daogang Peng, Yibo Guo, Nianlong Wang, Yuzhen Sun

Journal of System Simulation

Abstract: By analyzing the factors which affected the main-steam temperature, a multi-variable model was introduced to overcome the bad result of single variable cascade control. An improved differential evolution algorithm was proposed including mutation strategies random selection, crossover ratio and mutation ratio adaptive adjustment, which was used for closed-loop identification of main-steam multi-variable transfer function model. The principle and method how to obtain valid identification data from power plant distributed control system history database was introduced, and the data from some 1 000 MW coal-fired power plant was used to identify and verify the main-steam temperature multi-variable model, …

Research On Picking Robot Vision Localization Based On Semi-Physical Simulation, Keyin Chen, Xiangjun Zou, Hongxing Peng, Haiying Liang, Yuanchuang Hu

Journal of System Simulation

Abstract: Aiming at the problems of accuracy and stability of the vision localization based on physical picking robot, which were easy to make mistakes, long cycle, and not easy to be carried out indoors, a picking robot vision localization method based on the semi-physical simulation technology was proposed combining with the robot vision localization mechanism and robot kinematics. This method adopted the virtual picking robot to instead of the physical robot, and studied the vision localization of the fruit target in the virtual simulated environment, which was as the vision localization based on semi-physical simulation. The test results show that: …