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From the Bottom of the Heap by Gavin L. Simpson is, unless otherwise expressly stated, licensed under a Creative Commons Attribution 3.0 Unported License.
Permissions beyond the scope of this license may be available at ucfagls.wordpress.com.Gavin Simpson on Twitter
- @Jowanza if things were working before, why upgrade R until your workflow was secure? #rstats 21 hours ago
- @sjGoring Over several 1-hour sessions. Not really lectures - prefer more hands on with slides to keep things moving. 23 hours ago
- @sjGoring After that hook, I move on to domain-specific topics to get people doing things whilst learning R. Ramp up R level as you progress 1 day ago
- @sjGoring the plotting focus is to illustrate how a few simple commands gets you a publication quality figure etc. 1 day ago
- @sjGoring I've usually focussed on some basic R syntax/usage, then covered data import, and then got stuck into graphics/plotting 1 day ago
- @sjGoring these are ecology undergrads or grad students or beyond? 1 day ago
- @sjGoring to whom will you be teaching? (what level, what subject areas?) 1 day ago
- RT @figshare: figshare launches Publisher portals figshare.com/blog/figshare_… #PLOS: plos.figshare.com #F1000Research: http://t.co/KHwYuLdk… 1 day ago
- RT @KirkwoodLab: Insightful post by @mommiologist: The great escape: charting a career outside of academia wp.me/p2wMuW-1Ci via @Dyna… 2 days ago
- @l_marazzi Nope, hopefully attending the ESA meeting in Minneapolis around the same time though. 2 days ago
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Category Archives: Time series
What’s wrong with LOESS for palaeo data?
Locally weighted scatterplot smoothing (LOWESS) or local regression (LOESS) is widely used to highlight “signal” in variables from stratigraphic sequences. It is a user-friendly way of fitting a local model that derives its form from the data themselves rather than having … Continue reading
Posted in Palaeoecology, Palaeolimnology, R, Science, Time series
Tagged autocorrelation, cross-validation, GCV, LOESS, overfitting
4 Comments
Smoothing temporally correlated data
Something I have been doing a lot of work with recently are time series data, to which I have been fitting additive models to describe trends and other features of the data. When modelling temporally dependent data, we often need … Continue reading
Posted in R, Time series
4 Comments
Additive modelling and the HadCRUT3v global mean temperature series
Earlier, I looked at the HadCRUT3vgl data set using generalized least squares to investigate whether the trend in temperature since 1995 was statistically significant. Here I want to follow-up one of the points from the earlier posting; namely using a … Continue reading
Posted in Climate Change, R, Science, Time series
16 Comments
Global warming since 1995 ‘now significant’
Updated: 17 July 2011 Yesterday (June 11, 2011) the BBC reported on comments by Prof. Phil Jones, of the Climatic Research Unit (CRU), University of East Anglia (UEA), that the warming experienced by the planet since 1995 was statistically significant. … Continue reading
Posted in Climate Change, R, Science, Time series
17 Comments
Embedding a time series with time delay in R
I’ve recently been looking at Martin Trauth‘s book MATLAB® Recipes for Earth Sciences to try to understand what some of my palaeoceanography colleagues are doing with their data analyses (lots of frequency domain time series techniques and a preponderance of … Continue reading
Posted in R, Time series
3 Comments
