R (Computer program language)

Interactive and Dynamic Graphics for Data Analysis :with R and GGobi / by: (Language materials, printed)

The R book / by: (Language materials, printed)

Software for Data Analysis by: (Electronic resources)

Applied Spatial Data Analysis with R by: (Electronic resources)

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

Morphometrics with R by: (Language materials, printed)

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

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

A practical guide to ecological modellingusing R as a simulation platform / by: (Electronic resources)

Mixed effects models and extensions in ecology with R by: (Electronic resources)

R for SAS and SPSS users by: (Electronic resources)

A modern approach to regression with R by: (Electronic resources)

Applied statistical genetics with Rfor population-based association studies / by: (Electronic resources)

Permutation tests for stochastic ordering and ANOVAtheory and applications with R / by: (Electronic resources)

Bayesian computation with R by: (Electronic resources)

Introductory time series with R by: (Electronic resources)

A primer of ecology with R by: (Electronic resources)

Dynamic linear models with R by: (Electronic resources)

A beginner's guide to R by: (Electronic resources)

Functional Data Analysis with R and MATLAB by: (Electronic resources)

Statistics and data with R :an applied approach through examples / by: (Language materials, printed)

Hands-on intermediate econometrics using R :templates for extending dozens of practical examples / by: (Language materials, printed)

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

Time series analysis :with applications in R / by: (Language materials, printed)

R through Excela spreadsheet interface for statistics, data analysis, and graphics / by: (Electronic resources)

Bioconductor case studies by: (Electronic resources)

Using R for introductory statistics / by: (Language materials, printed)

Introducing Monte Carlo methods with R by: (Electronic resources)

Advances in social science research using R by: (Electronic resources)

Multivariate nonparametric methods with Ran approach based on spatial signs and ranks / by: (Electronic resources)

Introductory statistics with R by: (Electronic resources)

Introduction to probability simulation and Gibbs sampling with R by: (Electronic resources)

Ggplot2elegant graphics for data analysis / by: (Electronic resources)

R for Stata users by: (Electronic resources)

Using R for data management, statistical analysis, and graphics by: (Electronic resources)

Wavelet methods in statistics with R by: (Electronic resources)

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

Adaptive design theory and implementation using SAS and R / by: (Language materials, printed)

Probability and statistics with R / by: (Language materials, printed)

R graphics / by: (Language materials, printed)

An introduction to statistical inference and its applications with R / by: (Language materials, printed)

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

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

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

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

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

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

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

Computational statistics :an introduction to R / by: (Language materials, printed)

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

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

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

Environmental and ecological statistics with R / by: (Language materials, printed)

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

Forest analytics with Ran introduction / by: (Electronic resources)

Numerical ecology with R by: (Electronic resources)

A tiny handbook of R by: (Electronic resources)

An introduction to applied multivariate analysis with R by: (Electronic resources)

Data mining with Rattle and Rthe art of excavating data for knowledge discovery / by: (Electronic resources)

R for SAS and SPSS users by: (Electronic resources)

Data analysis and graphics using R :an example-based approach / by: (Language materials, printed)

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

Behavioral research data analysis with R by: (Electronic resources)

Competing risks and multistate models with R by: (Electronic resources)

Analysis of phylogenetics and evolution with R by: (Electronic resources)

Two-way analysis of variancestatistical tests and graphics using R / by: (Electronic resources)

Biostatistics with Ran introduction to statistics through biological data / by: (Electronic resources)

R by exampleconcepts to code / by: (Electronic resources)

Graphical models with R by: (Electronic resources)

Multivariate methods of representing relations in R for prioritization purposesselective scaling, comparative clustering, collective criteria and sequenced sets / by: (Electronic resources)

R graphics / by: (Language materials, printed)

An introduction to bootstrap methods with applications to R / by: (Language materials, printed)

Nonlinear regression with R / by: (Language materials, printed)

Biostatistical design and analysis using R :a practical guide / by: (Language materials, printed)

Solving differential equations in R by: (Electronic resources)

Six sigma with Rstatistical engineering for process improvement / by: (Electronic resources)

Multiple decrement models in Insurancean introduction using R / by: (Electronic resources)

Modeling psychophysical data in R by: (Electronic resources)

Hidden Markov models for time seriesan introduction using R / by: (Electronic resources)

Introduction to scientific programming and simulation using R by: (Electronic resources)

R programming for bioinformatics by: (Electronic resources)

Combinatorial pattern matching algorithms in computational biology using Perl and R by: (Electronic resources)

SAS and Rdata management, statistical analysis, and graphics / by: (Electronic resources)

Beginning Ran introduction to statistical programming / by: (Electronic resources)

Doing bayesian data analysis :a tutorial with R and BUGS / by: (Language materials, printed)

Statistical modelling in R / by: (Language materials, printed)

Statistical data analysis explainedapplied environmental statistics with R / by: (Electronic resources)

R and data miningexamples and case studies / by: (Electronic resources)

A handbook of statistical analyses using R by: (Electronic resources)

Data mining with Rlearning with case studies / by: (Electronic resources)

Exploratory multivariate analysis by example using R by: (Electronic resources)

Handbook of fitting statistical distributions with R by: (Electronic resources)

Introduction to data analysis with R for forensic scientists by: (Electronic resources)

Multiple comparisons using R by: (Electronic resources)

Clinical trial data analysis using R by: (Electronic resources)

A primer in biological data analysis and visualization using R / by: (Language materials, printed)

Circular statistics in R / by: (Language materials, printed)

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

Social media mining with R :deploy cutting-edge sentiment analysis techniques to real-world social media data using R / by: (Language materials, printed)

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

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

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

Bayesian essentials with R by: (Electronic resources)

XML and web technologies for data sciences with R by: (Electronic resources)

Introduction to data analysis and graphical presentation in biostatistics with Rstatistics in the large / by: (Electronic resources)

Statistical analysis of financial data in R by: (Electronic resources)

R quick syntax reference by: (Electronic resources)

Computational financean introductory course with R / by: (Electronic resources)

Contingency table analysismethods and implementation using R / by: (Electronic resources)

Statistical analysis of network data with R by: (Electronic resources)

Text analysis with R for students of literature by: (Electronic resources)

Using R for statistics by: (Electronic resources)

Getting Started with RAn introduction for biologists / by: (Electronic resources)

Statistics for linguistics with R a practical introduction / by: (Electronic resources)

Optimal experimental design with R by: (Electronic resources)

The R primer by: (Electronic resources)

An R companion to linear statistical models by: (Electronic resources)

Analysis of questionnaire data with R by: (Electronic resources)

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

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

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

Multistate analysis of life histories with R by: (Language materials, printed)

R for cloud computingan approach for data scientists / by: (Electronic resources)

Data mining applications with R by: (Electronic resources)

Beginning data science with R by: (Electronic resources)

R RecipesA Problem-Solution Approach / by: (Electronic resources)

Advanced R / by: (Language materials, printed)

Data science in R :a case studies approach to computational reasoning and problem solving / by: (Language materials, printed)

Parallel computing for data science :with examples in R, C++ and CUDA / by: (Language materials, printed)

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

Design and analysis of experiments with R / by: (Language materials, printed)

Displaying time series, spatial, and space-time data with R / by: (Language materials, printed)

Growth curve analysis and visualization using R / by: (Language materials, printed)

Multilevel modeling using R / by: (Language materials, printed)

Multiple factor analysis by example using R / by: (Language materials, printed)

Nonparametric statistical methods using R / by: (Language materials, printed)

Using R for introductory statistics / by: (Language materials, printed)

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

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

An introduction to R for quantitative economicsgraphing, simulating and computing / by: (Electronic resources)

R for marketing research and analytics by: (Electronic resources)

Spatial data analysis in ecology and agriculture using R by: (Electronic resources)

Analyzing financial data and implementing financial models using R by: (Electronic resources)

Adaptive tests of significance using permutations of residuals with R and SAS by: (Electronic resources)

Nonparametric hypothesis testingrank and permutation methods with applications in R / by: (Electronic resources)

Modern industrial statisticswith applications in R, MINITAB and JMP / by: (Electronic resources)

Basic data analysis for time series with R by: (Electronic resources)

Nonlinear parameter optimization using R tools by: (Electronic resources)

Doing Bayesian data analysisa tutorial with R, JAGS, and stan / by: (Electronic resources)

Mathematical statistics with applications in R by: (Electronic resources)

Primer to analysis of genomic Data using R by: (Electronic resources)

Applied multivariate statistics with R by: (Electronic resources)

Mastering R for quantitative finance :use R to optimize your trading strategy and build up your own risk management system / by: (Language materials, printed)

R cookbook / by: (Language materials, printed)

R for dummies / by: (Language materials, printed)

An introduction to analysis of financial data with R / by: (Language materials, printed)

Humanities data in Rexploring networks, geospatial data, images, and text / by: (Electronic resources)

Meta-analysis with R by: (Electronic resources)

Quality control with Ran ISO standards approach / by: (Electronic resources)

Beginning Ran introduction to statistical programming / by: (Electronic resources)

Statistical analysis and data displayan intermediate course with examples in R / by: (Electronic resources)

Political analysis using R by: (Electronic resources)

A user's guide to network analysis in R by: (Electronic resources)

Production and efficiency analysis with R by: (Electronic resources)

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

Mastering predictive analytics with R :master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts / by: (Language materials, printed)

Marketing data science :modeling techniques in predictive analytics with R and Python / by: (Language materials, printed)

Getting started with R :an introduction for biologists / by: (Language materials, printed)

Probability with applications and R / by: (Language materials, printed)

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

Geochemical modelling of igneous processes - principles and recipes in R languagebringing the power of R to a geochemical community / by: (Electronic resources)

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

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

Statistical hypothesis testing with SAS and R / by: (Language materials, printed)

Data mining and business analytics with R / by: (Language materials, printed)

R graphics by: (Electronic resources)

Learning analytics in R with SNA, LSA, and MPIA by: (Electronic resources)

R data analysis without programming by: (Electronic resources)

Examples in parametric inference with R by: (Electronic resources)

System dynamics modeling with R by: (Electronic resources)

Ggplot2elegrant graphics for data analysis / by: (Electronic resources)

Bayesian data analysis in ecology using linear models withR, Bugs, and Stan by: (Electronic resources)

Introduction to nonparametric statistics for the biological sciences using R by: (Electronic resources)

Data mining algorithmsexplained using R / by: (Electronic resources)

Spatial and spatio-temporal Bayesian models with R-INLA by: (Electronic resources)

Introduction to stochastic processes with R by: (Electronic resources)

Automated trading with Rquantitative research and platform development / by: (Electronic resources)

Latent variable modeling using R :a step-by-step guide / by: (Language materials, printed)

Working with the American community survey in Ra guide to using the acs package / by: (Electronic resources)

An introduction to data analysis using aggregation functions in R by: (Electronic resources)

Advanced Rdata programming and the cloud / by: (Electronic resources)

Learn business analytics in six steps using SAS and Ra practical, step-by-step guide to learning business analytics / by: (Electronic resources)

Text analysis with R for students of literature / by: (Language materials, printed)

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

A course in statistics with R / by: (Language materials, printed)

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

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

Introduction to statistics and data analysiswith exercises, solutions and applications in R / by: (Electronic resources)

Learn ggplot2 using shiny app by: (Electronic resources)

Using R for digital soil mapping by: (Electronic resources)

Machine learning using R by: (Electronic resources)

Business analytics using R - a practical approach by: (Electronic resources)

Data visualisation with R100 examples / by: (Electronic resources)

Applying test equating methodsusing R / by: (Electronic resources)

Functional programming in Radvanced statistical programming for data science, analysis and finance / by: (Electronic resources)

Joint models for longitudinal and time-to-event datawith applications in R / by: (Electronic resources)

Using R and RStudio for data management, statistical analysis, and graphics by: (Electronic resources)

Comparative approaches to using R and Python for statistical data analysis by: (Electronic resources)

The basics of item response theory using R by: (Electronic resources)

Financial risk modelling and portfolio optimization with R by: (Electronic resources)

Biostatistics and computer-based analysis of health data using R by: (Electronic resources)

Statistical disclosure control for microdatamethods and applications in R / by: (Electronic resources)

Bayesian cost-effectiveness analysis with the R package BCEA by: (Electronic resources)

Metaprogramming in Radvanced statistical programming for data science, analysis and finance / by: (Electronic resources)

Advanced object-oriented programming in Rstatistical programming for data science, analysis and finance / by: (Electronic resources)

Introduction to deep learning using Ra step-by-step guide to learning and implementing deep learning models using R / by: (Electronic resources)

Basic elements of computational statistics by: (Electronic resources)

Modern data science with R / by: (Language materials, printed)

Machine learning with R by: (Electronic resources)

Doubly classified model with R by: (Electronic resources)

Corpus linguistics and statistics with Rintroduction to quantitative methods in linguistics / by: (Electronic resources)

Computerized adaptive and multistage testing with Rusing packages catR and mstR / by: (Electronic resources)

Functional data structures in Radvanced statistical programming in R / by: (Electronic resources)

Numerical ecology with R by: (Electronic resources)

Business case analysis with Rsimulation tutorials to support complex business decisions / by: (Electronic resources)

R for programmersmastering the tools / by: (Electronic resources)

Applied probabilistic calculus for financial engineeringan introduction using R / by: (Electronic resources)

Python for R usersa data science approach / by: (Electronic resources)

Simulation and inference for stochastic processes with YUIMAa comprehensive R framework for SDEs and other stochastic processes / by: (Electronic resources)

Using R for data analysis in social sciences :a research project-oriented approach / by: (Language materials, printed)

Singular spectrum analysisusing R / by: (Electronic resources)

Pro machine learning algorithmsa hands-on approach to implementing algorithms in Python and R / by: (Electronic resources)

Applied analytics through case studies using SAS and Rimplementing predictive models and machine learning techniques / by: (Electronic resources)

Data science and predictive analyticsbiomedical and health applications using R / by: (Electronic resources)

Modern psychometrics with R by: (Electronic resources)

Oceanographic analysis with R by: (Electronic resources)

Epidemicsmodels and data using R / by: (Electronic resources)

Elements of Copula modeling with R by: (Electronic resources)

Semiparametric regression with R by: (Electronic resources)

Generalized linear models with examples in R by: (Electronic resources)

Spatial ecology and conservation modelingapplications with R / by: (Electronic resources)

Advanced statistics for the behavioral sciencesa computational approach wiith R / by: (Electronic resources)

Ensemble classification methods with applications in R / by: (Language materials, printed)

An R companion to applied regression. by: (Language materials, printed)

Probability, decisions and games :a gentle introduction using R / by: (Language materials, printed)

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

Sufficient dimension reduction :methods and application with R / by: (Language materials, printed)

R graphics / by: (Language materials, printed)

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

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

QCA with Ra comprehensive resource / by: (Electronic resources)

Learn R for applied statisticswith data visualizations, regressions, and statistics / by: (Electronic resources)

Advanced R statistical programming and data modelsanalysis, machine learning, and visualization / by: (Electronic resources)

R for finite element analyses of size-dependent microscale structures by: (Electronic resources)

R for marketing research and analytics by: (Electronic resources)

Machine learning using Rwith time series and industry-based use cases in R / by: (Electronic resources)

Deep learning with R by: (Electronic resources)

R quick syntax referencea pocket guide to the language, APIs and library / by: (Electronic resources)

Qualitative research using Ra systematic approach / by: (Electronic resources)

Time series analysis and its applicationswith R examples / by: (Electronic resources)

From experimental network to meta-analysismethods and applications with R for agronomic and environmental sciences / by: (Electronic resources)

Analyzing dependent data with vine copulasa practical guide with R / by: (Electronic resources)

Numerical analysis using Rsolutions to ODEs and PDEs / by: (Electronic resources)

R data science quick referencea pocket guide to APIs, libraries, and packages / by: (Electronic resources)

Data visualisation with R111 examples / by: (Electronic resources)

Applied time series analysis, with R / by: (Language materials, printed)

Nonlinear time series analysis with R / by: (Language materials, printed)

Discrete data analysis with R :visualization and modeling techniques for categorical and count data / by: (Language materials, printed)

Uncertainty analysis of experimental data with R / by: (Language materials, printed)

Introduction to unconstrained optimization with R by: (Electronic resources)

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

Introduction to data science :data analysis and prediction algorithms with R / by: (Language materials, printed)

Model-based clustering and classification for data science :with applications in R / by: (Language materials, printed)

Practical time series analysis :prediction with statistics and machine learning / by: (Language materials, printed)

Robust nonlinear regression :with application using R / by: (Language materials, printed)

Flexible regression and smoothing :using GAMLSS in R / by: (Language materials, printed)

A data scientist's guide to acquiring, cleaning, and managing data in R / by: (Language materials, printed)

Statistical analysis with R / by: (Language materials, printed)

Sound analysis and synthesis with R / by: (Language materials, printed)

Statistical rethinking :a Bayesian course with examples in R and Stan / by: (Language materials, printed)

Statistics for machine learning :techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R / by: (Language materials, printed)

Multivariate time series analysis :with R and financial applications / by: (Language materials, printed)

An introduction to R for spatial analysis & mapping / by: (Language materials, printed)

Multivariate statistical quality control using R / by: (Language materials, printed)

Quantile regression for cross-sectional and time series dataapplications in energy markets using R / by: (Electronic resources)

Text analysis with Rfor students of literature / by: (Electronic resources)

Introduction to R for terrestrial ecologybasics of numerical analysis, mapping, statistical tests and advanced application of R / by: (Electronic resources)

Using R for trade policy analysisR codes for the UNCTAD and WTO practical guide / by: (Electronic resources)

Quantitative economics with Ra data science approach / by: (Electronic resources)

Applied multiple imputationadvantages, pitfalls, new developments and applications in R / by: (Electronic resources)

Data envelopment analysis with R by: (Electronic resources)

Introduction to probabilistic and statistical methods with examples in R by: (Electronic resources)

Statistical analysis of network data with R by: (Electronic resources)

Financial analytics with Rbuilding a laptop laboratory for data science / by: (Electronic resources)

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

The R primer by: (Electronic resources)

Statistical analysis of questionnairesa unified approach based on R and Stata / by: (Electronic resources)

Advanced R 4 data programming and the cloudusing PostgreSQL, AWS, and Shiny / by: (Electronic resources)

Easy statistics for food science with R by: (Electronic resources)

Exploratory multivariate analysis by example using R by: (Electronic resources)

R and MATLAB by: (Electronic resources)

Chemometrics with Rmultivariate data analysis in the natural and life sciences / by: (Electronic resources)

An introduction to clustering with R by: (Electronic resources)

Random forests with R by: (Electronic resources)

Spatial relationships between two georeferenced variableswith applications in R / by: (Electronic resources)

Retirement income recipes in Rfrom ruin probabilities to intelligent drawdowns / by: (Electronic resources)

Statistical learning with math and R100 exercises for building logic / by: (Electronic resources)

Advanced analytics in power BI with R and Pythoningesting, transforming, visualizing / by: (Electronic resources)

Beginning R 4from beginner to pro / by: (Electronic resources)

Practical R 4applying R to data manipulation, processing and integration / by: (Electronic resources)

R companion to elementary applied statistics / by: (Language materials, printed)

Insights from data with R :an introduction for the life and environmental sciences / by: (Language materials, printed)

Analyzing spatial models of choice and judgment / by: (Language materials, printed)

Algebraic analysis of social networks :models, methods & applications using R / by: (Language materials, printed)

Basic statistics with R :reaching decisions with data / by: (Language materials, printed)

R for political data science :a practical guide / by: (Language materials, printed)

Using R for Bayesian spatial and spatio-temporal health modeling / by: (Language materials, printed)

Applied meta-analysis with R and Stata / by: (Language materials, printed)

Statistics with R :solving problems using real-world data / by: (Language materials, printed)

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

A step-by-step guide to exploratory factor analysis with R and Rstudio / by: (Language materials, printed)

Data analysis with Rstudio :an easygoing introduction / by: (Language materials, printed)

An introduction to clustering with R / by: (Language materials, printed)

Statistical regression modeling with Rlongitudinal and multi-level modeling / by: (Electronic resources)

CRAN recipesDPLYR, Stringr, Lubridate, and RegEx in R / by: (Electronic resources)

Pricing export credita concise framework with examples and implementation code in R / by: (Electronic resources)

Luminescencedata analysis and modeling using R / by: (Electronic resources)

A course on small area estimation and mixed modelsmethods, theory and applications in R / by: (Electronic resources)

Machine learning for factor investing / by: (Language materials, printed)

Using R for biostatistics by: (Electronic resources)

Statistical methods for overdispersed count data by: (Electronic resources)

Measuring productivity in education and not-for-profitswith tools and examples in R / by: (Electronic resources)

Analyzing financial data and implementing financial models using R by: (Electronic resources)

Sparse estimation with math and R100 exercises for building logic / by: (Electronic resources)

An introduction to statistical learningwith applications in R / by: (Electronic resources)

Modern optimization with R by: (Electronic resources)

Business statistics with solutions in R by: (Electronic resources)

Biomarker analysis in clinical trials with R by: (Electronic resources)

Univariate, bivariate, and multivariate statistics using Rquantitative tools for data analysis and data science / by: (Electronic resources)

SAS for R usersa book for budding data scientists / by: (Electronic resources)

Bootstrap methodswith applications in R / by: (Electronic resources)

Applied statisticstheory and problem solutions with R / by: (Electronic resources)

Permutation statistical methods with R by: (Electronic resources)

Partial least squares structural equation modeling (PLS-SEM) using Ra workbook / by: (Electronic resources)

Geostatistics for compositional data with R by: (Electronic resources)

Data analytics :a small data approach / by: (Language materials, printed)

Virus host cell genetic material transportcomputational ode/pde modeling with R / by: (Electronic resources)

Pro data visualization using R and Javascriptanalyze and visualize key data on the web / by: (Electronic resources)

Kernel methods for machine learning with Math and R100 exercises for building logic / by: (Electronic resources)

Multilayer networksanalysis and visualization : introduction to muxViz with R / by: (Electronic resources)

R 4 quick syntax referencea pocket guide to the language, API's and library / by: (Electronic resources)

Applied social network analysis with Remerging research and opportunities / by: (Electronic resources)

Applied hierarchical modeling in ecologyanalysis of distribution, abundance and species richness in R and BUGS.Volume 2,Dynamic and advanced models / by: (Electronic resources)

Mixture and hidden markov models with R by: (Electronic resources)

Beginning data science in R 4data analysis, visualization, and modelling for the data scientist / by: (Electronic resources)

Data visualization for social and policy researcha step-by-step approach using R and Python / by: (Electronic resources)

R for health data science by: (Electronic resources)

A tour of data sciencelearn R and Python in parallel / by: (Electronic resources)

Supervised machine learningoptimization framework and applications with SAS and R / by: (Electronic resources)

Biometry for forestry and environmental data with examples in R by: (Electronic resources)

Panel data econometrics with R by: (Electronic resources)

Introduction to mathematics for economics with R by: (Electronic resources)

Bayes factors for forensic decision analyses with R by: (Electronic resources)

R 4 data science quick referencea pocket guide to APIs, libraries, and packages / by: (Electronic resources)

Probability, statistics and simulationwith application programs written in R / by: (Electronic resources)

Applied multivariate statistics with R by: (Electronic resources)

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

Practical statistics for data scientists :50+ essential concepts using R and Python / by: (Language materials, printed)

Introductory applied statisticswith resampling methods & R / by: (Electronic resources)

Computational finance with R by: (Electronic resources)

Uncertainty quantification using R by: (Electronic resources)

Working with data in public healtha practical pathway with R / by: (Electronic resources)

Construction analyticsforecasting and investment valuation / by: (Electronic resources)

Essentials of Excel VBA, Python, and R.Volume II,Financial derivatives, risk management and machine learning by: (Electronic resources)

Practical business analytics using R and Pythonsolve business problems using a data-driven approach / by: (Electronic resources)

Hyperparameter tuning for machine and deep learning with Ra practical guide / by: (Electronic resources)

Epidemicsmodels and data using R / by: (Electronic resources)

Applied linear regression for business analytics with Ra practical guide to data science with case studies / by: (Electronic resources)

Applied calculus with R by: (Electronic resources)

Functional programming in R 4advanced statistical programming for data science, analysis, and finance / by: (Electronic resources)

Spatial socio-econometric modeling (SSEM)a low-code toolkit for spatial data science and interactive visualizations using R / by: (Electronic resources)

Biostatistics with 'R'a guide for medical doctors / by: (Electronic resources)

Practicing R for statistical computing by: (Electronic resources)

Behavior analysis with machine learning using R by: (Electronic resources)

Probabilitywith applications and R / by: (Electronic resources)

WAIC and WBIC with R Stan100 exercises for building logic / by: (Electronic resources)

Introduction to stochastic processes using R by: (Electronic resources)

Elements of data science, machine learning, and artificial intelligence using R by: (Electronic resources)

Spatio-temporal trend analysis of rainfall using R software and ArcGISa case study of an agro-climatic zone-1 of Gujarat, India / by: (Electronic resources)

Visualization and imputation of missing valueswith applications in R / by: (Electronic resources)

Applications of regression for categorical outcomes using R / by: (Language materials, printed)

Data science in practice / by: (Language materials, printed)

Telling stories with data :with applications in R / by: (Language materials, printed)

ANOVA and mixed models :a short introduction using R / by: (Language materials, printed)

Bayesian multilevel models for repeated measures data :a conceptual and practical introduction in R / by: (Language materials, printed)

The statistical analysis of doubly truncated data :with applications in R / by: (Language materials, printed)

Categorical data analysis and multilevel modeling using R / by: (Language materials, printed)

The Conway-Maxwell-Poisson distribution / by: (Language materials, printed)

Bayesian networks :with examples in R / by: (Language materials, printed)

Handbook of graphs and networks in people analytics :with examples in R and python / by: (Language materials, printed)

Learning microeconometrics with R / by: (Language materials, printed)

Stochastic processes with R :an introduction / by: (Language materials, printed)

Learning analytics methods and tutorialsa practical guide using R / by: (Electronic resources)

Regression-based normative data for psychological assessmenta hands-on approach using R / by: (Electronic resources)

Uncertainty quantification with RBayesian methods / by: (Electronic resources)

Model-based clustering and classification for data sciencewith applications in R / by: (Electronic resources)

Introduction to statistics in human performanceusing SPSS and R / by: (Electronic resources)

Handbook of regression modeling in people analyticswith examples in R and Python / by: (Electronic resources)

Applied regularization methods for the social sciences by: (Electronic resources)

The R book by: (Electronic resources)

Introduction to probability, statistics & Rfoundations for data-based sciences / by: (Electronic resources)

R programmingstatistical data analysis in research / by: (Electronic resources)

Business analytics with R and Python by: (Electronic resources)

Geographic data analysis using R by: (Electronic resources)

Complex-valued econometrics with examples in Rmodelling, regression and applications / by: (Electronic resources)

Humanities data in Rexploring networks, geospatial data, images, and text / by: (Electronic resources)

Artificial intelligence and machine learning with Rapplications in the field of business analytics / by: (Electronic resources)

R for basic biostatistics in medical research by: (Electronic resources)

Applied statisticsmethods using R / by: (Electronic resources)

R by example by: (Electronic resources)

Health analytics with Rlearning data science using examples from healthcare and direct-to-consumer genetics / by: (Electronic resources)

R for political science researchan introduction for absolute beginners / by: (Electronic resources)

Statistical causal mediation analysis with R by: (Electronic resources)

Introduction to statistics using R / by: (Language materials, printed)

Foundations of statistics for data scientists :with R and Python / by: (Language materials, printed)

Spatial sampling with R / by: (Language materials, printed)

The R book / by: (Language materials, printed)

Predictive analytics :parametric models for regression and classification using R / by: (Language materials, printed)

Nonparametric statistical methods using R / by: (Language materials, printed)

Elements of network sciencetheory, methods and applications in Stata, R and Python / by: (Electronic resources)

Cultural data sciencean introduction to R / by: (Electronic resources)

Time series analysis and its applicationswith R examples / by: (Electronic resources)

Predictive analytics with SAS and Rcore concepts, tools, and implementation / by: (Electronic resources)

Data insight foundationsstep-by-step data analysis with R / by: (Electronic resources)

Text analytics for corpus linguistics and digital humanitiessimple R scripts and tools / by: (Electronic resources)

An introduction to R and Python for data analysisa side-by-side approach / by: (Electronic resources)

Cluster analysisa primer using R / by: (Electronic resources)

R applications in earth sciencesfrom soil data to climate time series analysis and modeling / by: (Electronic resources)

Statistical learning in geneticsan introduction using R / by: (Electronic resources)

Data science : foundations and hands-on experiencehandling economic, spatial, and multidimensional data with R / by: (Electronic resources)

Introduction to FinTech using Excelin an R-assisted learning environment / by: (Electronic resources)