大葉大學圖書館 |

Works:	107 works in 68 publications in 68 languages

Titles

Behavioral research data analysis with R[electronic resource] / by: (Language materials, printed)

Competing risks and multistate models with R[electronic resource] / by: (Language materials, printed)

Analysis of phylogenetics and evolution with R[electronic resource] / by: (Language materials, printed)

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

Biostatistics with R[electronic resource] :an introduction to statistics through biological data / by: (Language materials, printed)

R by example[electronic resource] :concepts to code / by: (Language materials, printed)

Graphical models with R[electronic resource] / by: (Language materials, printed)

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

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

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

R programming for bioinformatics[electronic resource] / by: (Language materials, printed)

Combinatorial pattern matching algorithms in computational biology using Perl and R[electronic resource] / by: (Language materials, printed)

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

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

Statistical data analysis explained[electronic resource] :applied environmental statistics with R / by: (Language materials, printed)

R and data mining[electronic resource] :examples and case studies / by: (Language materials, printed)

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

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

Exploratory multivariate analysis by example using R[electronic resource] / by: (Language materials, printed)

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

Introduction to data analysis with R for forensic scientists[electronic resource] / by: (Language materials, printed)

Multiple comparisons using R[electronic resource] / by: (Language materials, printed)

Clinical trial data analysis using R[electronic resource] / by: (Language materials, printed)

Statistics for linguistics with R [electronic resource]:a practical introduction / by: (Language materials, printed)

Data mining applications with R[electronic resource] / by: (Language materials, printed)

Getting Started with R[electronic resource] :An introduction for biologists / by: (Language materials, printed)

Optimal experimental design with R[electronic resource] / by: (Language materials, printed)

The R primer[electronic resource] / by: (Language materials, printed)

An R companion to linear statistical models[electronic resource] / by: (Language materials, printed)

Analysis of questionnaire data with R[electronic resource] / by: (Language materials, printed)

Business analytics and data mining with R[electronic resource] / by: (Language materials, printed)

Computational finance[electronic resource] :an introductory course with R / by: (Language materials, printed)

Contingency table analysis[electronic resource] :methods and implementation using R / by: (Language materials, printed)

Statistical analysis of network data with R[electronic resource] / by: (Language materials, printed)

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

Using R for statistics[electronic resource] / by: (Language materials, printed)

Spatial data analysis in ecology and agriculture using R[electronic resource] / by: (Language materials, printed)

Bayesian essentials with R[electronic resource] / by: (Language materials, printed)

XML and web technologies for data sciences with R[electronic resource] / by: (Language materials, printed)

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

Statistical analysis of financial data in R[electronic resource] / by: (Language materials, printed)

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

Mathematical statistics with applications in R[electronic resource] / by: (Language materials, printed)

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

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

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

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

Nonlinear parameter optimization using R tools[electronic resource] / by: (Language materials, printed)

Primer to analysis of genomic Data using R[electronic resource] / by: (Electronic resources)

Applied multivariate statistics with R[electronic resource] / by: (Language materials, printed)

Humanities data in R[electronic resource] :exploring networks, geospatial data, images, and text / by: (Language materials, printed)

Meta-analysis with R[electronic resource] / by: (Language materials, printed)

Quality control with R[electronic resource] :an ISO standards approach / by: (Language materials, printed)

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

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

Political analysis using R[electronic resource] / by: (Language materials, printed)

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

Production and efficiency analysis with R[electronic resource] / by: (Language materials, printed)

Learning analytics in R with SNA, LSA, and MPIA[electronic resource] / by: (Language materials, printed)

Examples in parametric inference with R[electronic resource] / by: (Language materials, printed)

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

R graphics[electronic resource] / by: (Language materials, printed)

Bayesian data analysis in ecology using linear models withR, Bugs, and Stan[electronic resource] / by: (Electronic resources)

System dynamics modeling with R[electronic resource] / by: (Electronic resources)

Ggplot2[electronic resource] :elegrant graphics for data analysis / by: (Electronic resources)

Data mining algorithms[electronic resource] :explained using R / by: (Electronic resources)

Spatial and spatio-temporal Bayesian models with R-INLA[electronic resource] / by: (Electronic resources)

Introduction to stochastic processes with R[electronic resource] / by: (Electronic resources)

Introduction to nonparametric statistics for the biological sciences using R[electronic resource] / by: (Electronic resources)

Automated trading with R[electronic resource] :quantitative research and platform development / by: (Electronic resources)

Working with the American community survey in R[electronic resource] :a guide to using the acs package / by: (Electronic resources)

Learning social media analytics with R :transform data from social media platforms into actionable insights / 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)

An introduction to data analysis using aggregation functions in R[electronic resource] / by: (Language materials, printed)

Advanced R[electronic resource] :data programming and the cloud / by: (Language materials, printed)

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

Learn ggplot2 using shiny app[electronic resource] / by: (Language materials, printed)

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

Using R and RStudio for data management, statistical analysis, and graphics[electronic resource] / by: (Language materials, printed)

Comparative approaches to using R and Python for statistical data analysis[electronic resource] / by: (Language materials, printed)

Statistical data cleaning with applications in R / by: (Language materials, printed)

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

Habitat suitability and distribution models with applications in R / by: (Language materials, printed)

R for programmers[electronic resource] :mastering the tools / by: (Electronic resources)

The R primer[electronic resource] / by: (Electronic resources)

Statistical analysis of questionnaires[electronic resource] :a unified approach based on R and Stata / by: (Electronic resources)

Exploratory multivariate analysis by example using R[electronic resource] / by: (Electronic resources)

R and MATLAB[electronic resource] / by: (Electronic resources)

Numerical analysis using R[electronic resource] :solutions to ODEs and PDEs / by: (Electronic resources)

Financial analytics with R[electronic resource] :building a laptop laboratory for data science / by: (Electronic resources)

Numerical integration of space fractional partial differential equations.Vol 1,Introduction to algorithms and computer coding in R / by: (Electronic resources)

Easy statistics for food science with R[electronic resource] / by: (Electronic resources)

Applied social network analysis with R[electronic resource] :emerging research and opportunities / by: (Electronic resources)

R for health data science[electronic resource] / by: (Electronic resources)

A tour of data science[electronic resource] :learn R and Python in parallel / by: (Electronic resources)

Supervised machine learning[electronic resource] :optimization framework and applications with SAS and R / by: (Electronic resources)

Biometry for forestry and environmental data with examples in R[electronic resource] / by: (Electronic resources)

Panel data econometrics with R[electronic resource] / by: (Electronic resources)

Business statistics with solutions in R[electronic resource] / by: (Electronic resources)

Biomarker analysis in clinical trials with R[electronic resource] / by: (Electronic resources)

Univariate, bivariate, and multivariate statistics using R[electronic resource] :quantitative tools for data analysis and data science / by: (Electronic resources)

SAS for R users[electronic resource] :a book for budding data scientists / by: (Electronic resources)

Applied statistics[electronic resource] :theory and problem solutions with R / by: (Electronic resources)

Behavior analysis with machine learning using R[electronic resource] / by: (Electronic resources)

Probability[electronic resource] :with applications and R / by: (Electronic resources)

R (Computer program language)