Publications by
Somalia Sorghum April 2023
Introduction This is the Somalia April Sorghum forecast report from the GB model. The goal is to assist users in evaluating current forecasts in the context of past forecasts and to translate the forecast component into key assumptions about food security. The report includes the following key components: A verbal summary of assumptions based on t...
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Somalia Sorghum March 2023
Introduction This is the Somalia March Sorghum forecast report. The goal is to assist users in evaluating current forecasts in the context of past forecasts and to translate the forecast component into key assumptions about food security. The report includes the following key components: A verbal summary of assumptions based on the statistics in t...
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Somalia Sorghum December 2022
Introduction This is the Somalia December Sorghum forecast report. The goal is to assist users in evaluating current forecasts in the context of past forecasts and to translate the forecast component into key assumptions about food security. The report includes the following key components: A verbal summary of assumptions based on the statistics...
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Plotting forecast() objects in ggplot part 1: Extracting the Data
Lately I’ve been using Rob J Hyndman‘s excellent forecast package. The package comes with some built in plotting functions but I found I wanted to customize and make my own plots in ggplot. In order to do that, I need a generalizable function that will extract all the data I want (forecasts, fitted values, training data, actual observations i...
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Plotting forecast() objects in ggplot part 2: Visualize Observations, Fits, and Forecasts
In my last post I presented a function for extracting data from a forecast() object and formatting the data so that it can be plotted in ggplot. The scenario is that you are fitting a model to a time series object with training data, then forecasting out, and then visually evaluating the fit with the observations that your forecast tried to dup...
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R Structure Explained
This post by Suraj Gupta explains it all. This is the firs time I have seen a concise and accessible explanation of the R environment structure and why it matters. Addendum: This one by Digithead is also pretty good Related To leave a comment for the author, please follow the link and comment on their blog: Frank Davenport's Blog on R, Stat...
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R in the CPB and the role of Open Source in Promoting Transparency and Austerity
The Revolution blog links to an O’Reilly interview with two CIO’s from the Consumer Protection Bureau. The gist of the interview is “Open Source is Great, we are using it for everything; R and Big Data are the next hot thing, et cetera”. I don’t mean to belittle those points, as I mostly agree them, but they are covered well in both...
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The Epic Search for the Perfect R Text Editor
I can never seem to get exactly what I want from an R text editor. Let me correct that, I can never seem to get exactly what I want from an R text editor on a MAC. I used to use Tinn-R which met most my needs: Free,lightweight with an easy install and a slim UI Good commenting and code folding tools Customizable short cuts Support for mult...
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Notes from A Recent Spatial R Class I Gave
Below is a link to a pdf (compiled with the amazing knitr package) and some accompanying data for a recent short course I gave on basic spatial data import/analysis/visualization in R. The class was only two hours and some of the participants were being exposed to R for the first time so the material is limited. The class was a follow up to a pre...
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Prototype Forecast Report
Introduction This is a protype forecast report. The goal is to assist users in assessing how an earth observation product can be used for making agricultural outlooks. Four figures are shown: Mean Area, Production, and Yield over the years 1994 to 2014 -This provides context for interpreting the grain data Mean, Current Value, and Current Anomal...
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