R (Computer program language)

Applied calculus with R by: (Language materials, printed)

Applied linear regression for business analytics with R = a practical guide to data science with case studies / by: (Language materials, printed)

Applied multivariate statistics with R by: (Language materials, printed)

Probability, statistics and simulation = with application programs written in R / by: (Language materials, printed)

Panel data econometrics with R by: (Language materials, printed)

Biometry for forestry and environmental data with examples in R by: (Language materials, printed)

Supervised machine learning = optimization framework and applications with SAS and R / by: (Language materials, printed)

A tour of data science = learn R and Python in parallel / by: (Language materials, printed)

R for health data science by: (Language materials, printed)

Applied hierarchical modeling in ecology = analysis of distribution, abundance and species richness in R and BUGS.. Volume 2,. Dynamic and advanced models / by: (Language materials, printed)

Applied social network analysis with R = emerging research and opportunities / by: (Language materials, printed)

Interactive web-based data visualization with R, plotly, and shiny / by: (Language materials, printed)

Retirement income recipes in R : = from ruin probabilities to intelligent drawdowns / by: (Language materials, printed)

Analyzing financial data and implementing financial models using R / by: (Language materials, printed)

Easy R : = access, prepare, visualize, explore data, and write papers / by: (Language materials, printed)

Applied statistics = theory and problem solutions with R / by: (Language materials, printed)

Statistical methods for overdispersed count data by: (Language materials, printed)

SAS for R users = a book for budding data scientists / by: (Language materials, printed)

Univariate, bivariate, and multivariate statistics using R = quantitative tools for data analysis and data science / by: (Language materials, printed)

Biomarker analysis in clinical trials with R by: (Language materials, printed)

Business statistics with solutions in R by: (Language materials, printed)

Machine learning using R : = with time series and industry-based use cases in R / by: (Language materials, printed)

Lattice = Multivariate Data Visualization with R / by: (Language materials, printed)

Data mining with R : = learning with case studies / by: (Language materials, printed)

Applied multivariate statistics with R by: (Language materials, printed)

Forest analytics with R = an introduction / by: (Language materials, printed)

Numerical ecology with R by: (Language materials, printed)

A tiny handbook of R by: (Language materials, printed)

Statistical methods for environmental epidemiology with R = a case study in air pollution and health / by: (Language materials, printed)

An introduction to applied multivariate analysis with R by: (Language materials, printed)

Morphometrics with R by: (Language materials, printed)

Introductory statistics with R by: (Language materials, printed)

Applied Spatial Data Analysis with R by: (Language materials, printed)

Analysis of integrated and cointegrated time series with R by: (Language materials, printed)

Applied Econometrics with R by: (Language materials, printed)

R through Excel = a spreadsheet interface for statistics, data analysis, and graphics / by: (Language materials, printed)

Wavelet methods in statistics with R by: (Language materials, printed)

Ggplot2 = elegant graphics for data analysis / by: (Language materials, printed)

R and data mining = examples and case studies / by: (Language materials, printed)

Data mining with Rattle and R = the art of excavating data for knowledge discovery / by: (Language materials, printed)

R for SAS and SPSS users by: (Language materials, printed)

A handbook of statistical analyses using R by: (Language materials, printed)

Data mining with R = learning with case studies / by: (Language materials, printed)

Exploratory multivariate analysis by example using R by: (Language materials, printed)

Handbook of fitting statistical distributions with R by: (Language materials, printed)

Introduction to data analysis with R for forensic scientists by: (Language materials, printed)

Multiple comparisons using R by: (Language materials, printed)

Clinical trial data analysis using R by: (Language materials, printed)

Using R for data management, statistical analysis, and graphics by: (Language materials, printed)

Statistical analysis and data display = an intermediate course with examples in R / by: (Language materials, printed)

Political analysis using R by: (Language materials, printed)

A user's guide to network analysis in R by: (Language materials, printed)

Beginning R = an introduction to statistical programming / by: (Language materials, printed)

Graphics for statistics and data analysis with R / by: (Language materials, printed)

Humanities data in R = exploring networks, geospatial data, images, and text / by: (Language materials, printed)

Meta-analysis with R by: (Language materials, printed)

Quality control with R = an ISO standards approach / by: (Language materials, printed)

Production and efficiency analysis with R by: (Language materials, printed)

Statistical data analysis explained = applied environmental statistics with R / by: (Language materials, printed)

Combinatorial pattern matching algorithms in computational biology using Perl and R by: (Language materials, printed)

Hidden Markov models for time series = an introduction using R / by: (Language materials, printed)

Introduction to scientific programming and simulation using R by: (Language materials, printed)

R programming for bioinformatics by: (Language materials, printed)

SAS and R = data management, statistical analysis, and graphics / by: (Language materials, printed)

Qualitative comparative analysis with R = a user's guide / by: (Language materials, printed)

Statistical computing in C++ and R / by: (Language materials, printed)

Linear mixed-effects models using R = a step-by-step approach / by: (Language materials, printed)

Understanding statistics using R by: (Language materials, printed)

Introduction to image processing using R = learning by examples / by: (Language materials, printed)

Bayesian networks in R = with applications in systems biology / by: (Language materials, printed)

Seamless R and C++ integration with Rcpp by: (Language materials, printed)

An introduction to statistical learning = with applications in R / by: (Language materials, printed)

Applied spatial data analysis with R by: (Language materials, printed)

Guide to programming and algorithms using R by: (Language materials, printed)

Analyzing compositional data with R by: (Language materials, printed)

Pro data visualization using R and JavaScript by: (Language materials, printed)

Beginning R = an introduction to statistical programming / by: (Language materials, printed)

Modeling psychophysical data in R by: (Language materials, printed)

Six sigma with R = statistical engineering for process improvement / by: (Language materials, printed)

Multiple decrement models in Insurance = an introduction using R / by: (Language materials, printed)

Solving differential equations in R by: (Language materials, printed)

EnvStats = an R package for environmental statistics / by: (Language materials, printed)

The R software = fundamentals of programming and statistical analysis / by: (Language materials, printed)

Analysis of phylogenetics and evolution with R by: (Language materials, printed)

Behavioral research data analysis with R by: (Language materials, printed)

Competing risks and multistate models with R by: (Language materials, printed)

Two-way analysis of variance = statistical tests and graphics using R / by: (Language materials, printed)

Biostatistics with R = an introduction to statistics through biological data / by: (Language materials, printed)

R by example = concepts to code / by: (Language materials, printed)

Graphical models with R by: (Language materials, printed)

Multivariate methods of representing relations in R for prioritization purposes = selective scaling, comparative clustering, collective criteria and sequenced sets / by: (Language materials, printed)

A practical guide to ecological modelling = using R as a simulation platform / by: (Language materials, printed)

Mixed effects models and extensions in ecology with R by: (Language materials, printed)

R for SAS and SPSS users by: (Language materials, printed)

A modern approach to regression with R by: (Language materials, printed)

Applied statistical genetics with R = for population-based association studies / by: (Language materials, printed)

Permutation tests for stochastic ordering and ANOVA = theory and applications with R / by: (Language materials, printed)

Bayesian computation with R by: (Language materials, printed)

Introductory time series with R by: (Language materials, printed)

Optimal experimental design with R by: (Language materials, printed)

The R primer by: (Language materials, printed)

An R companion to linear statistical models by: (Language materials, printed)

Analysis of questionnaire data with R by: (Language materials, printed)

Business analytics and data mining with R by: (Language materials, printed)

Statistics for linguistics with R = a practical introduction / by: (Language materials, printed)

Data mining applications with R by: (Language materials, printed)

Getting Started with R = An introduction for biologists / by: (Language materials, printed)

Bayesian essentials with R by: (Language materials, printed)

Introduction to data analysis and graphical presentation in biostatistics with R = statistics in the large / by: (Language materials, printed)

XML and web technologies for data sciences with R by: (Language materials, printed)

Statistical analysis of financial data in R by: (Language materials, printed)

Doing Bayesian data analysis = a tutorial with R, JAGS, and stan / by: (Language materials, printed)

Mathematical statistics with applications in R by: (Language materials, printed)

Big data analytics with R and Hadoop : = set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics / by: (Language materials, printed)

Adaptive tests of significance using permutations of residuals with R and SAS DUP_1 by: (Language materials, printed)

Nonparametric hypothesis testing DUP_1 = rank and permutation methods with applications in R / by: (Language materials, printed)

Basic data analysis for time series with R DUP_1 by: (Language materials, printed)

Nonlinear parameter optimization using R tools DUP_1 by: (Language materials, printed)

Spatial data analysis in ecology and agriculture using R by: (Language materials, printed)

Adaptive tests of significance using permutations of residuals with R and SAS by: (Language materials, printed)

Nonlinear parameter optimization using R tools by: (Language materials, printed)

Nonparametric hypothesis testing = rank and permutation methods with applications in R / by: (Language materials, printed)

Modern industrial statistics = with applications in R, MINITAB and JMP / by: (Language materials, printed)

Basic data analysis for time series with R by: (Language materials, printed)

R data analysis without programming by: (Language materials, printed)

R graphics by: (Language materials, printed)

Data mining algorithms : = explained using R / by: (Language materials, printed)

Analyzing financial data and implementing financial models using R / by: (Language materials, printed)

Geochemical modelling of igneous processes - principles and recipes in R language = bringing the power of R to a geochemical community / by: (Language materials, printed)

Learning analytics in R with SNA, LSA, and MPIA by: (Language materials, printed)

Examples in parametric inference with R by: (Language materials, printed)

System dynamics modeling with R by: (Language materials, printed)

Ggplot2 = elegrant graphics for data analysis / by: (Language materials, printed)

Introduction to nonparametric statistics for the biological sciences using R by: (Language materials, printed)

Automated trading with R = quantitative research and platform development / by: (Language materials, printed)

Working with the American community survey in R = a guide to using the acs package / by: (Language materials, printed)

An introduction to data analysis using aggregation functions in R by: (Language materials, printed)

Advanced R = data programming and the cloud / by: (Language materials, printed)

Learn business analytics in six steps using SAS and R = a practical, step-by-step guide to learning business analytics / by: (Language materials, printed)

Introduction to statistics and data analysis = with exercises, solutions and applications in R / by: (Language materials, printed)

Learn ggplot2 using shiny app by: (Language materials, printed)

Testing R code / by: (Language materials, printed)

Joint models for longitudinal and time-to-event data = with applications in R / by: (Language materials, printed)

Using R and RStudio for data management, statistical analysis, and graphics by: (Language materials, printed)

Comparative approaches to using R and Python for statistical data analysis by: (Language materials, printed)

Financial risk modelling and portfolio optimization with R / by: (Language materials, printed)

Data science in higher education : = step-by-step machine learning for institutional researchers / by: (Language materials, printed)

Biostatistics and computer-based analysis of health data using R by: (Language materials, printed)

The basics of item response theory using R by: (Language materials, printed)

Statistical disclosure control for microdata = methods and applications in R / by: (Language materials, printed)

Bayesian cost-effectiveness analysis with the R package BCEA by: (Language materials, printed)

Applied surrogate endpoint evaluation methods with SAS and R / by: (Language materials, printed)

Data mining algorithms = explained using R / by: (Language materials, printed)

Spatial and spatio-temporal Bayesian models with R-INLA by: (Language materials, printed)

Introduction to stochastic processes with R by: (Language materials, printed)

Metaprogramming in R = advanced statistical programming for data science, analysis and finance / by: (Language materials, printed)

Advanced object-oriented programming in R = statistical programming for data science, analysis and finance / by: (Language materials, printed)

Applied probabilistic calculus for financial engineering = an introduction using R / by: (Language materials, printed)

Python for R users = a data science approach / by: (Language materials, printed)

Data analysis with R : = a comprehensive guide to manipulating, analyzing, and visualizing data in R / by: (Language materials, printed)

Machine learning with R by: (Language materials, printed)

Doubly classified model with R by: (Language materials, printed)

Corpus linguistics and statistics with R = introduction to quantitative methods in linguistics / by: (Language materials, printed)

Computerized adaptive and multistage testing with R = using packages catR and mstR / by: (Language materials, printed)

Functional data structures in R = advanced statistical programming in R / by: (Language materials, printed)

Introduction to deep learning using R = a step-by-step guide to learning and implementing deep learning models using R / by: (Language materials, printed)

Basic elements of computational statistics by: (Language materials, printed)

Numerical ecology with R by: (Language materials, printed)

Business case analysis with R = simulation tutorials to support complex business decisions / by: (Language materials, printed)

Simulation and inference for stochastic processes with YUIMA = a comprehensive R framework for SDEs and other stochastic processes / by: (Language materials, printed)

Singular spectrum analysis = using R / by: (Language materials, printed)

Pro machine learning algorithms = a hands-on approach to implementing algorithms in Python and R / by: (Language materials, printed)

Applied analytics through case studies using SAS and R = implementing predictive models and machine learning techniques / by: (Language materials, printed)

Data science and predictive analytics = biomedical and health applications using R / by: (Language materials, printed)

Modern psychometrics with R by: (Language materials, printed)

Oceanographic analysis with R by: (Language materials, printed)

Epidemics = models and data using R / by: (Language materials, printed)

Generalized linear models with examples in R by: (Language materials, printed)

Elements of Copula modeling with R by: (Language materials, printed)

Semiparametric regression with R by: (Language materials, printed)

R graphics cookbook : = practical recipes for visualizing data / by: (Language materials, printed)

Applied probabilistic calculus for financial engineering : = an introduction using R / by: (Language materials, printed)

Panel data econometrics with R / by: (Language materials, printed)

An introduction to the advanced theory of nonparametric econometrics : = a replicable approach using R / by: (Language materials, printed)

Deep learning with R by: (Language materials, printed)

R quick syntax reference = a pocket guide to the language, APIs and library / by: (Language materials, printed)

Qualitative research using R = a systematic approach / by: (Language materials, printed)

Time series analysis and its applications = with R examples / by: (Language materials, printed)

From experimental network to meta-analysis = methods and applications with R for agronomic and environmental sciences / by: (Language materials, printed)

Analyzing dependent data with vine copulas = a practical guide with R / by: (Language materials, printed)

R for programmers = mastering the tools / by: (Language materials, printed)

Numerical analysis using R = solutions to ODEs and PDEs / by: (Language materials, printed)

Software for Data Analysis by: (Language materials, printed)

R for data science : = import, tidy, transform, visualize, and model data / by: (Language materials, printed)

Using R for digital soil mapping by: (Language materials, printed)

Machine learning using R by: (Language materials, printed)

Business analytics using R - a practical approach by: (Language materials, printed)

Data visualisation with R = 100 examples / by: (Language materials, printed)

Applied hierarchical modeling in ecology. = analysis of distribution, abundance and species richness in R and BUGS /. Volume 1,. Prelude and static models by: (Language materials, printed)

Financial analytics with R = building a laptop laboratory for data science / by: (Language materials, printed)

The R primer by: (Language materials, printed)

Statistical analysis of questionnaires = a unified approach based on R and Stata / by: (Language materials, printed)

Easy statistics for food science with R by: (Language materials, printed)

Exploratory multivariate analysis by example using R by: (Language materials, printed)

R and MATLAB by: (Language materials, printed)