I write differently from what I speak, I speak differently from what I think, I think differently from the way I ought to think, and so it all proceeds into deepest darkness.
Franz Kafka
Category: books (Page 2 of 4)
At the moment I am writing R code that involves a lot of simulation for a project. This time I wanted to organize the work properly, put a package together, document it,… the whole shebang. Hadley Wickham has excellent documentation for this process in Advanced R, which works very well as a website. Up to this point there is nothing new; but the material is also available as a book.
At this point in my life I do not want to have a physical object if I can avoid it. On top of that, code tutorials work a lot better as a website, so one can copy, paste and experiment. PDF or ebooks are not very handy for this subject either. Here enters a revolutionary notion: I like to pay people who do a good job and, in the process, make my job easier but sometimes I do not want an object in exchange.
‘No estaba muerto, andaba the parranda’† as the song says. Although rather than partying it mostly has been reading, taking pictures and trying to learn how to record sounds. Here there are some things I’ve come across lately.
I was having a conversation with an acquaintance about courses that were particularly useful in our work. My forestry degree involved completing 50 compulsory + 10 elective† courses; if I had to choose courses that were influential and/or really useful they would be Operations Research, Economic Evaluation of Projects, Ecology, 3 Calculus and 2 Algebras. Subsequently my PhD was almost entirely research based but I sort of did Matrix Algebra: Dorian lent me his copy of Searle’s Matrix Algebra Useful for Statistics and passed me a pile of assignments that Shayle Searle used to give in his course in Cornell. I completed the assignments on my own pace and then sat a crazy take-home exam for 24 hours.
Forestry is the province of variability. From a spatial point of view this variability ranges from within-tree variation (e.g. modeling wood properties) to billions of trees growing in millions of hectares (e.g. forest inventory). From a temporal point of view we can deal with daily variation in a physiological model to many decades in an empirical growth and yield model. Therefore, it is not surprising that there is a rich tradition of statistical applications to forestry problems.
At the same time, the scope of statistical problems is very diverse. As the saying goes forestry deals with “an ocean of knowledge, but only one centimeter deep”, which is perhaps an elegant way of saying a jack of all trades, master of none. Forest Analytics with R: an introduction by Andrew Robinson and Jeff Hamann (FAWR hereafter) attempts to provide a consistent overview of typical statistical techniques in forestry as they are implemented using the R statistical system.