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Programming with Big Data in R (pbdR) – a series of R packages enhanced by SPMD parallelism for big data analysis; R Commander – GUI interface for R; Rattle GUI – GUI interface for R; Revolution Analytics – production-grade software for the enterprise big data analytics; RStudio – GUI interface and development environment for R; ROOT ...
Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [2] [3] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...
RQDA is an R package for computer-assisted qualitative data analysis or CAQDAS, making it one of the few open source tools to assist qualitative coding of textual data.Note that there are also other popular but mostly proprietary CAQDAS tools such as NVivo and Atlas.ti but these software come at a cost.
The significantly reorganized revised edition of the book (2023) [2] expands and modernizes the presented mathematical principles, computational methods, data science techniques, model-based machine learning and model-free artificial intelligence algorithms. The 14 chapters of the new edition start with an introduction and progressively build ...
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]
This includes object-oriented data-handling and analysis tools for data from Affymetrix, cDNA microarray, and next-generation high-throughput sequencing methods. [28] Homepage for R-Forge. R-Forge, [29] is a central platform for the collaborative development of R packages, R-related software, and projects. R-Forge also hosts many unpublished ...