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R for everyone : advanced analytics and graphics / Jared P. Lander.

By: Material type: TextTextSeries: Addison-Wesley data and analytics seriesPublisher: Boston : Addison-Wesley, [2017]Copyright date: ©2017Edition: Second editionDescription: xxiv, 528 pages : illustrations (some color) ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 013454692X
  • 9780134546926
Subject(s): DDC classification:
  • 311 23 LAN P19R
LOC classification:
  • QA76.73.R3 L36 2017
Contents:
Getting R -- The R environment -- R packages -- Basics of R -- Advanced data structures -- Reading data into R -- Statistical graphics -- Writing R functions -- Control statements -- Loops, the Un-R way to iterate -- Group manipulation -- Faster group manipulation with dplyr -- Iterating with purrr -- Data reshaping -- Reshaping data in the Tidyverse -- Manipualting strings -- Probability distributions -- Basic statistics -- Linear models -- Generalized linear models -- Model diagnostics -- Regularization and shrinkage -- Nonlinear models -- Time series and autocorrelation -- Clustering -- Model fitting with Caret -- Reproducibility and reports with knitr -- Rich documents with RMarkdown -- Interactive dashboards with shiny -- Building R packages -- Real-life resources.
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Holdings
Item type Current library Home library Call number Status Date due Barcode
Books Books NIRDPR LIBRARY NIRDPR LIBRARY 311 LAN P19R (Browse shelf(Opens below)) Available 113717

Includes indexes.

Getting R -- The R environment -- R packages -- Basics of R -- Advanced data structures -- Reading data into R -- Statistical graphics -- Writing R functions -- Control statements -- Loops, the Un-R way to iterate -- Group manipulation -- Faster group manipulation with dplyr -- Iterating with purrr -- Data reshaping -- Reshaping data in the Tidyverse -- Manipualting strings -- Probability distributions -- Basic statistics -- Linear models -- Generalized linear models -- Model diagnostics -- Regularization and shrinkage -- Nonlinear models -- Time series and autocorrelation -- Clustering -- Model fitting with Caret -- Reproducibility and reports with knitr -- Rich documents with RMarkdown -- Interactive dashboards with shiny -- Building R packages -- Real-life resources.

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