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R Tutorial for Oceanographers

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Oceanographic Analysis with R

Abstract

R comes with an excellent tutorial that, like many fine tutorials, tends to be ignored by people with little patience for material presented in a general manner. This is why the present chapter uses oceanographic examples to explain R concepts, and why code makes up so much of the text. The early examples are designed to encourage readers to become comfortable whilst navigating the R documentation, because this skill can be the key to moving from simple examples to real-world applications. The main concepts of R data types and language features are illustrated here in practical terms, with many of the explanations involving graphical representation. Since experienced R users are unlikely to study this chapter in great depth, specialized methods of oceanographic analysis are mainly deferred to succeeding chapters.

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Notes

  1. 1.

    http://cran.r-project.org/.

  2. 2.

    The package count was inferred from web archives at http://wayback.archive.org/.

  3. 3.

    http://github.com .

  4. 4.

    The indented lines of the Makefile must start with a tab character, not spaces.

  5. 5.

    R displays a prompt before the input, but this is omitted throughout this book.

  6. 6.

    A subtle point is that R does not always look up the values of variables until they are needed. This is related to R concepts of “lazy evaluation ” and “promises ”.

  7. 7.

    www.iana.org/time-zones.

  8. 8.

    Alternative time origins may be specified to as.POSIXlt() , and this can be helpful in working with times represented in other systems such as SPSS and SAS .

  9. 9.

    This profile results from a nonlinear regression (Sect. 2.5.5.2) of the oxygen profile at station 112 of the section dataset in the ocedata package.

  10. 10.

    See http://www.gnu.org/software/gsl/ for more on GSL.

  11. 11.

    Note the use of the UNESCO equation of state here; with the GSW equation, longitude and latitude would also have to be supplied; see Sect. 5.2.1 and Appendix D.

  12. 12.

    Readers who wish to learn more details of object orientation in R might start with Chambers (2008) or Wickham (2014).

  13. 13.

    For more on performance issues, see Appendix E.

  14. 14.

    See Sect. 5.7 for more on Argo floats.

  15. 15.

    Several coastline resolutions are provided in the ocedata and oce packages.

  16. 16.

    Home electricity provides a dramatic illustration. Although voltage measurements may give a confidence interval on the mean that barely departs from 0V, the measurement uncertainty will indicate that any given measurement could easily be of order 100V. That is why electrical outlets must be covered up, in houses with young children.

  17. 17.

    Note the use of set.seed( ) to let readers reconstruct the example.

  18. 18.

    It is unwise to use hypothesis tests without considering their limitations. Some issues of misapplication are outlined by, e.g., Johnson and Omland (2004) and Hauer (2004), and deep concerns about the misuse of p values are raised in a highly influential editorial in The American Statistician (Wasserstein and Lazar 2016).

  19. 19.

    If p < 2.2 × 10−16, R regression summaries simply reports “p-value: <2.2e-16”.

  20. 20.

    See also the NISTnls package, which provides data and code for statistical test suites developed by researchers at the U.S. National Institute for Standards and Technology.

  21. 21.

    An alternative to stack() is melt() , from the reshape2 package (Wickham 2007). If this is used, then aov() must use value for values and variable for ind.

  22. 22.

    It is not strictly necessary to use as.ctd() to create a "ctd" object, but it makes it easier to create a standardized plot with isopycnals.

  23. 23.

    A test with a 90 Mb file on the author’s machine revealed read_csv() to be nearly 6 times faster than read.csv() .

  24. 24.

    http://www.cgd.ucar.edu/cas/catalog/climind/SOI.signal.ascii.

  25. 25.

    http://www.cgd.ucar.edu/cas/catalog/climind/SOI.signal.ascii.

  26. 26.

    https://www.nodc.noaa.gov/OC5/woa13/woa13data.html.

  27. 27.

    https://www.rstudio.com/products/shiny.

  28. 28.

    http://shiny.rstudio.com/gallery/plot-interaction-exclude.html.

  29. 29.

    RStudio has a variety of other helpful features, e.g. a code-completing editor and a code-analysis tool that can recommend alterations that may make code more robust.

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Authors and Affiliations

  1. Oceanography, Dalhousie University, Halifax, NS, Canada

    Dan E. Kelley

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  1. Dan E. Kelley
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Kelley, D.E. (2018). R Tutorial for Oceanographers. In: Oceanographic Analysis with R. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-8844-0_2

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