Monthly Archives: September 2009

Workflow in R

September 17, 2009
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This came up recently on StackOverflow. One of the answers was particularly helpful and I plan to adopt this for my future work. In fact, it is close to what I already do, but is a little more structured. The idea is to break the code into four files, ...

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Solar Trends: Sunspot Numbers Since 1749

September 17, 2009
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Solar Trends: Sunspot Numbers Since 1749

This is the 1st in a series of  posts I will be doing on solar trends. In this post, I show how to retrieve online monthly sunspot data back to 1749, calculate average annual sunspot numbers (SSN),  plot the monthly and annual average SSN as well as a lowess smooth, add the Solar

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Example 7.12: Calculate and plot a running average

September 17, 2009
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Example 7.12: Calculate and plot a running average

The Law of Large Numbers concerns the stability of the mean, as sample sizes increase. This is an important topic in mathematical statistics. The convergence (or lack thereof, for certain distributions) can easily be visualized in SAS and R (see also Horton, Qian and Brown, 2004).Assume that X1, X2, ..., Xn are independent and identically distributed realizations...

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Comments on “Introduction to Scientific Programming and Simulation Using R”

September 17, 2009
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Comments on “Introduction to Scientific Programming and Simulation Using R”

I've just been reading Introduction to Scientific Programming and Simulation Using R by Owen Jones, Robert Maillardet, and Andrew Robinson. It seems like it would make a good introductory book for a course on, as the title suggests, scientific programm...

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R clinic this week: Regression Modeling Strategies in R

September 16, 2009
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At this week's R clinic Frank Harrell will unveil the new rms (Regression Modeling Strategies) package that is a replacement for the R Design package.  He will demonstrate the differences with Design, especially related to enhanced graphics for displaying effects in regression models.  Frank will also discuss the implementation of quantile regression in rms.  The rms package website has...

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Multiple Linear Regression

September 14, 2009
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Multiple Linear Regression

A multiple linear regression (MLR) model that describes a dependent variable y by independent variables x1, x2, ..., xp (p > 1) is expressed by the equation as follows, where the numbers α and βk (k = 1, 2, ..., p) are the parameter...

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Find the function you’re looking for in R

September 14, 2009
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Any R user no matter what level of experience has had trouble finding the package or the function to do what you want to do and then figuring out how to use it.  The sos package in R just made that a lot easier.First, fire up R, then install the sos package (don't omit the quotes):install.packages("sos") It'll ask you to...

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Chicago Half Marathon 2009

September 13, 2009
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Today it was once again time for the Chicago Half Marathon (which I have now been running in 2003, 2004, 2005, 2006, 2007 and 2008). Conditions were much much better than last year's very heavy rainfall---we were once again treated to a sunny and clear Chicago sky. It was however a little on the humid side and got...

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Finding an R function

September 13, 2009
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Finding an R function

Suppose you want a function to fit a neural network. What’s the best way to find it? Here are three steps that help to find the elusive function relatively quickly. First, use help.search("neural") or the shorthand ??neural. This will search the help files of installed packages for the word “neural”. Actually, fuzzy matching is used

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Finding an R function

September 13, 2009
By

Suppose you want a function to fit a neural network. What’s the best way to find it? Here are three steps that help to find the elusive function relatively quickly. First, use help.search("neural") or the shorthand ??neural. This will search the help...

Read more »