Monthly Archives: November 2012

Earthquakes Over the Past 7 Days

This is a brief example using the maps in R and to highlight a source of data.  This is real-time data and it comes from the U.S. Geological Survey.  This shows the location of earthquakes with magnitude of at least 1.0 in the lower 48 states. library(maps) library(maptools) library(rgdal) eq = read.table(file="http://earthquake.usgs.gov/earthquakes/catalogs/eqs7day-M1.txt", fill=TRUE, sep=",", header=T) plot.new()… Read More »

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Hurricane Sandy Land Wind Speed and Kriging

NJ Hurricane Sandy Landfall Data These data come from the National Climatic Data Center (NCDC).  Using the above link will download all of the data collected by the NCDC on the day of Hurricane Sandy.  The data can also be obtained directly from the source at http://cdo.ncdc.noaa.gov/qclcd/QCLCD. The purpose of this post is not a discussion… Read More »

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What Time Is It?

A common scenario that I run into is time and how to deal with it. I often will do a  variety of summaries and analysis that need to be measured at different points in time. Whether I want to graph the data or review the results I need to be able to perform measurements relative… Read More »

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One Big Number That’s Not Big Enough

32-bit systems pose an interesting problem because of some of its limitations. These systems are only capable of handling an integer that is  .   That is a fairly large number but it just not large enough.  That is particularly true if that number is a phone number (e.g. (214)748-3647).  As you can see there… Read More »

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Using R to Compare Hurricane Sandy and Hurricane Irene

Having just lived through two back to back hurricanes (Irene in 2011 and Sandy in 2012) that passed through the New York metro area I was curious how the paths of the hurricanes differed.  I worked up a quick graph in R using data from Unisys.  The data also includes wind speed and barometric pressure.… Read More »

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Mapping Capabilities in R

From time-to-time creating a basic map of the United States or other parts of the world to complement some statistical analysis is useful to emphasize a point. The maps package in R provide a good way to produce these these maps.  These maps axes are based on latitude and longitude so overlaying other information on… Read More »

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