2684 search results for "map"

Analyzing baseball data with R

November 27, 2013
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Analyzing baseball data with R

This week, the post is an interview with Max Marchi. Max is the author, with Jim Albert, of the book "Analyzing baseball data with R". Hi, Max. Welcome back to MilanoR. Last time you wrote for us a series of … Continue reading →

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Five ways to handle Big Data in R

November 27, 2013
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Five ways to handle Big Data in R

Big data was one of the biggest topics on this year’s useR conference in Albacete and it is definitely one of today’s hottest buzzwords. But what defines “Big Data”? And on the practical side: How can big data be tackled in R? What data is big? Hadley Wickham, one of the best known R developers,

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New R package raincpc: Obtain and Analyze Rainfall data from the Climate Prediction Center (CPC)

November 26, 2013
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The Climate Prediction Center's (CPC) daily rainfall data for the entire world, 1979 - present & 50-km resolution, is one of the few high quality and long term observation-based rainfall products. Data is available at CPC's ftp site. However, it is...

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R & GGPLOT – Expanded Plots

November 26, 2013
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R & GGPLOT – Expanded Plots

>>GET THE R CODE<< R and GGPLOT are great! There are some things, however, that I want to be able to do easily. For these things I have to create template codes, which I want to share with you! This time around I wanted to show you how you can create “zoomed” areas of a

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How can R and Hadoop be used together?

November 26, 2013
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How can R and Hadoop be used together?

By inspired from this Quora question, I have been started working on how can R and Hadoop integrated to be used together? By very hard verification process, finally I got the possible ways to use R and Hadoop together for performing Big Data Analytics. This blog post is written with consideration of helping to a The post How...

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Installing rgdal in Ubuntu 13.04

November 26, 2013
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The Geospatial Data Abstraction Library (GDAL) is a workhorse of digital mapping. Written in c++, it underpins many online and desktop geoprocessing programs including QGIS and GeoServer. Through its OGR library, GDAL enables the import and export of most common spatial data formats, including the trusty ESRI Shapefile. These features and more make access to GDAL capabilities critical for...

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Installing rgdal in Ubuntu 13.04

November 26, 2013
By

The Geospatial Data Abstraction Library (GDAL) is a workhorse of digital mapping. Written in c++, it underpins many online and desktop geoprocessing programs including QGIS and GeoServer. Through its OGR library, GDAL enables the import and export of most common spatial data formats, including the trusty ESRI Shapefile. These features and more make access to GDAL capabilities critical for...

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Getting Started with Mixed Effect Models in R

November 25, 2013
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Getting Started with Multilevel Modeling in R Getting Started with Multilevel Modeling in R Jared E. Knowles Introduction Analysts dealing with grouped data and complex hierarchical structures in their data ranging from measurements nested within participants, to counties nested within states or students nested within classrooms often find themselves...

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New R package emdatr: Global Disaster Losses from the EM-DAT Database

November 22, 2013
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The International Disaster Database EM-DAT from the Center for Research on the Epidemiology of Disasters (CRED, Belgium) is often used as a reference for losses on human life and property resulting from natural and man-made disasters. This databas...

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Comparison Among Groups with Francis Parameterization

November 21, 2013
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Comparison Among Groups with Francis Parameterization

In my last post, I suggested that the Francis parameterization of the von Bertalanffy growth model may be used in cases where the typical parameterization did not converge (likely due to issues related to highly correlated parameters and data with … Continue reading →

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