Resources
======================

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There are many excellent resources on the web related to my interests.

The R environment
---------------------------

* `Stat 545 <https://stat545.com/>`__ (Bryan) "Data wrangling, exploration, and analysis with R".

    A good first introduction to R.

* `R Markdown <https://rmarkdown.rstudio.com/>`__

   Reproducible research with R and Python

* `CRAN task views <https://cran.r-project.org/web/views/>`__

   "Provide some guidance about which packages on CRAN are relevant for tasks related to a certain topic. They give a brief overview of the included packages."

Data Science
-----------------

* `R for Data Science <https://r4ds.had.co.nz/>`__ (Grolemund, Wickham):

    "How to get your data into R, get it into the most useful structure, transform it, visualise it and model it". Uses the ``tidyverse``.

* `The Elements of Statistical Learning:  Data Mining, Inference, and Prediction <http://web.stanford.edu/~hastie/ElemStatLearn/>`__ (Hastie, Tibshirani, Friedman):

    The standard text

* `An Introduction to Statistical Learning with Applications in R <http://faculty.marshall.usc.edu/gareth-james/ISL/>`__ (James, Witten, Hastie, Tibshirani)

    A simplification of "The Elements...", suitable for a first course.

Spatial statistics & analysis
---------------------------------------

* `Spatial Data Science with R <https://rspatial.org/raster/index.html>`__  (Robert Hijmans, UC Davis)

    Introduction to R,  Spatial data manipulation with R,  Spatial data analysis,  Remote sensing image analysis, Species Distribution Modeling with R, Case studies

* `Geospatial Data Science in R <https://zia207.github.io/geospatial-r-github.io/>`__ (Zia Ahmed, University at Buffalo)

    Spatial Data Processing, Spatial Statistics, Spatial Interpolation, Remote Sensing Data Processing and Analysis

* `Geospatial Data Science in Python <https://zia207.github.io/geospatial-python.io/>`__ (Zia Ahmed, University at Buffalo)

    Spatial Data Processing, Spatial/Geo-Statistics, Remote Sensing Data Processing and Analysis

* `Workshop: Applied Spatial Statistics in R <http://www.people.fas.harvard.edu/~zhukov/spatial.html>`__ (Yuri M. Zhukov,  Harvard University)

* `CRAN task view: analysis of spatial data <https://cran.r-project.org/web/views/Spatial.html>`__ (Bivand)

    Categorizes and reviews R packages for spatial data, raster data, geographic metadata, reading and writing spatial data, geospatial data sources, data processing, data cleaning, thematic cartography, web mapping, point pattern analysis, geostatistics, disease mapping and areal data analysis, spatial regression, ecological analysis, 

* :download:`E-{Z} Kriging: Ordinary Kriging Explained <../_static/legacy_sw/E_Z_Kriging_Program_and_Manual.zip>` (Dennis Walvoort, 	Wageningen Environmental Research)

   An interactive Windows 3.1 program to experiment with Ordinary Kriging, along with a PDF explanation and tutorial. Distributed by permission.

.. meta::
   :description: D G Rossiter's professional pages -- resources
   :keywords: R, spatial statistics, data science

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