Course detail

LCF5876 - Computation in R Environment Applications in Ecology and Forest Resources

Credit hours

In-class work
per week
per week
15 weeks
120 hours

João Luis Ferreira Batista

To develop proficiency in computing in the R environment for the implementation of quantitative methods in research in Ecology and Forest Resources.

1. Introduction: history and philosophy of working in R environment.
2. Fast course in R: a quick presentation of the basic elements for working in R
3. Functional Structure of R: mathematical functions, logic functions and probability distribution functions
4. R as object oriented programming environment: “everything is object”, types of objects, class and other object attributes
5. The SQL data organization structures: the concept of table, link and query
6. Data in R: reading the data, types of variables, types of data objects
7. Data computation: summaries, aggregation and merging
8. Exploratory graphical data analysis: basic functions and “lattice” package
9. Introduction to Linear Models: statistical “formula”, the rational of statistical modeling in R, linear regression and analysis of variance
10. Simulation: simulation based on probability distribution functions, the simulation of a linear model
11. Resampling: resampling techniques for variance estimation, simulation for confidence envelopes
12. Advanced data computation: indexing, subsetting, data correction, matrix and arrays
13. Programming your own functions in R: function definition, processing and result
14. S language programming: flux control, vectorial procedures, assignment
15. Object oriented programming in S4 language: creating new classes and methods

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Frost, J. 2013 Regression Analysis: How Do I Interpret R-squared and Assess the Goodness-of-Fit? The Minitab Blog online,
Kabacoff, R. R in Action. New York: Manning Publication, 2011.
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R Development Team. R Data Import/Export—Version 3.1.2 (2014-10-31). Manual online,
R Development Team. R Language Definition—Version 3.1.2 (2014-10-31). Manual online,
Robinson, A.P.; Hamann, J.D. Forest Analytics with R: An Introduction. New York: Springer, 2011.
Venables,W.N.; Smith, D.M.; R Development Team; An Introduction to R—Version 2.9.2 (2009-08-04). Manual online,
Venables,W.N.; Ripley, B.D.; Modern Applied Statistics with S. New York: Springer, 2002.
Venables, W.N.; Ripley, B.D.; S Programming. New York: Springer, 2000.