8 posts · 7,264 views
notes for statistics, R, eco-modeling … without regards to the past … randomly …
apeescape
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- October 25, 2010
- 01:16 AM
- 623 views
Parametric Bootstrap Power Analysis of GISS Temp Data
by apeescape in mind of a Markov chain
Previosly, I calculated a bunch of ad-hoc power curves from GISTEMP data. Power is essentially a reframing of the p-value, to see the significance of the trend lines in the global temps. However, power calculations are inherently very noisy, hence, my ad-hoc way of aggregating the data. Another method is to bootstrap through the responses [...]... Read more »
Gerard, P., Smith, D., & Weerakkody, G. (1998) Limits of Retrospective Power Analysis. The Journal of Wildlife Management, 62(2), 801. DOI: 10.2307/3802357
- August 26, 2010
- 03:35 AM
- 735 views
Global Temperature Proxy Reconstructions ~ now with CO2 forcing
by apeescape in mind of a Markov chain
Previously, I did a simple Bayesian projection of recent temperature using proxy data and the methods shown in McShane and Wyner (2010). I showed that when you take out the last 30 years of data (1969~1998), the projection does not track the recent uptick in temperatures well. The “projection” is a simple unparametric bootstrap which [...]... Read more »
BLAKELEY B. MCSHANE AND ABRAHAM J. WYNER. (2010) A STATISTICAL ANALYSIS OF MULTIPLE TEMPERATURE PROXIES: ARE RECONSTRUCTIONS OF SURFACE TEMPERATURES OVER THE LAST 1000 YEARS RELIABLE?. Annals of Applied Statistics, 4(3). info:/
- August 22, 2010
- 04:10 AM
- 665 views
Global Temperature Proxy Reconstructions ~ Bayesian extrapolation of warming w/ rjags
by apeescape in mind of a Markov chain
There are a bunch of “hockey sticks” that calculate past global temps. through the use of proxies when instrumental data is absent. There is a new one out there by McShane and Wyner (2010) that’s creating quite a stir in the blogosphere (here, here, here, here). The main take out being, that the uncertainty is [...]... Read more »
BLAKELEY B. MCSHANE AND ABRAHAM J. WYNER. (2010) A STATISTICAL ANALYSIS OF MULTIPLE TEMPERATURE PROXIES: ARE RECONSTRUCTIONS OF SURFACE TEMPERATURES OVER THE LAST 1000 YEARS RELIABLE?. Annals of Applied Statistics, 4(3). info:/
Mann, M., Zhang, Z., Hughes, M., Bradley, R., Miller, S., Rutherford, S., & Ni, F. (2008) Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proceedings of the National Academy of Sciences, 105(36), 13252-13257. DOI: 10.1073/pnas.0805721105
- August 5, 2010
- 06:52 PM
- 1,241 views
R and Google Earth ~ comparing tuna tracks vs. Gulf of Mexico oil spill extent
by apeescape in mind of a Markov chain
There is a lot of interest in how the Gulf of Mexico oil gusher will affect the ecosystem and its marine species. One such species is the Western Atlantic bluefin tuna that holds the Gulf of Mexico as one of its major spawning grounds. Recent tag data show that the location of the gusher is [...]... Read more »
Teo SL, & Block BA. (2010) Comparative influence of ocean conditions on yellowfin and atlantic bluefin tuna catch from longlines in the gulf of Mexico. PloS one, 5(5). PMID: 20526356
- July 18, 2010
- 12:07 AM
- 1,012 views
Cherry Picking to Generalize ~ retrospective meta-power analysis using Cohen’s f^2 of NASA temp visualization
by apeescape in mind of a Markov chain
Previously, I plotted a grid of NASA GISS global temps in ggplot2 to show general trends by the brute force method. Here, I will again use the brute force method to do a simple power analysis on a portion of the data (data here). The general aim is to figure out what the minimum sample [...]... Read more »
Thomas, L. (1997) Retrospective Power Analysis. Conservation Biology, 11(1), 276-280. DOI: 10.1046/j.1523-1739.1997.96102.x
- July 9, 2010
- 09:35 PM
- 1,058 views
Log Normal Distributions in Ecology ~ multiplications complications
by apeescape in mind of a Markov chain
The normal distribution is the “norm” when applying statistics to data. It is simple to interpret, simple to predict, simple to optimize, convenient software-wise and analytically elegant. But in many applications, this modeling assumption may not be optimal. The first is that the normal distribution doesn’t have a zero bound. In ecology, the data is [...]... Read more »
LIMPERT, E., STAHEL, W., & ABBT, M. (2001) Log-normal Distributions across the Sciences: Keys and Clues. BioScience, 51(5), 341. DOI: 10.1641/0006-3568(2001)051[0341:LNDATS]2.0.CO;2
- July 5, 2010
- 01:44 PM
- 996 views
FAO Tuna Fisheries Catch Trends in the Pacific Ocean and the China Anomaly ~ EDA of one year differences
by apeescape in mind of a Markov chain
In 2001, Reg Watson and Daniel Pauly published a paper in Nature (“Systematic distortions in world fisheries catch trends”) that showed anomalous trends for China’s marine fisheries catch trends. They took fisheries catch data within various countries’ EEZs and saw the difference between the predicted catch and the observed catch. China apparently had catches exponentially [...]... Read more »
Watson, R., & Pauly, D. (2001) Systematic distortions in world fisheries catch trends. Nature, 414(6863), 534-536. DOI: 10.1038/35107050
- June 27, 2010
- 09:03 PM
- 934 views
Plot Multiple Time Series using the flow/inkblot/river/ribbon/volcano/hourglass/area/whatchamacallit plots ~ blue whale catch per country w/ ggplot2
by apeescape in mind of a Markov chain
Ever since I first looked at this NYT visualization by Amanda Cox, I’ve always wanted to reproduce this in R. This is a plot that stacks multiple time series onto one another, with the width of the river/ribbon/hourglass representing the strength at each time. The NYT article used box office revenue as the width of the river. It’s also an interactive web app. thanks to some help from graphic designers.... Read more »
Havre, S., Hetzler, E., Whitney, P., & Nowell, L. (2002) ThemeRiver: visualizing thematic changes in large document collections. IEEE Transactions on Visualization and Computer Graphics, 8(1), 9-20. DOI: 10.1109/2945.981848
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