Publications by Cory Lesmeister
Chicken or the Egg? Granger-Causality for the masses
When I first learned about Granger-causality this past February, I was bemused and quite skeptical of the whole procedure. I felt it belonged on the scrapheap of impractical academic endeavors, preferring to possibly use an ARIMA transfer function model for the same task. However, several contemporaries threw the red challenge flag and upon f...
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Fear and Loathing in Data Science 2013-06-11 20:25:00
Related To leave a comment for the author, please follow the link and comment on their blog: Fear and Loathing in Data Science. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job. Want to share your content on R-blogg...
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Getting started with R
I wanted to avoid advanced topics in this post and focus on some “blocking and tackling” with R in an effort to get novices started. This is some of the basic code I found useful when I began using R just over 6 weeks ago.Reading in data from a .csv file is a breeze with this command.> data = read.csv(file.choose())No need to have your own ...
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Partial Least Squares Regression in R
Partial Least Squares Regression:This week I will be doing some consulting around Structural Equation Modeling (SEM) techniques to solve a unique business problem. We are trying to identify customer preference for various products and traditional regression is not adequate because of the high dimensional component to the data set along with the...
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A Quick and Dirty Guide to Exploratory Data Visualization
One of the things I’ve noticed teaching statistical fundamentals or working with colleagues is the lack of focus on first visually exploring the data. Novices seem to want to jump right in with correlations and statistical tests without getting a “feel” of what they are examining. The Germans have an appropriate term I think in “finge...
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Postscript to Data Visualization
Much to my chagrin, I realized I forgot to include one of the more interesting features in the lattice package. You can quickly turn a quantitative variable into one of levels of equal counts. This provides a nice way of looking at slices of your data in a trellis plot. These slices are referred to as shingles as they overlap acco...
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Quandl.com for Time Series Datasets
If you want to dig in with both feet on time series data, then quandl.com is a good choice. The website claims to have several million datasets all of them available for free download. It also allows you to upload data to the site with an authentication token.Well, the site says it is easy to get data from their API directly into R, so let’...
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Changepoint Analysis of Time Series?
Last time we downloaded data from quandl.com. This was privately-owned homes completed in a month in thousands of units(not seasonally adjusted). Now, let’s take a look at some basic R functions to examine time series along with my first exploration of what I feel is an intriguing package called “changepoint”. Please note that this is...
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Time Series Decomposition
In the last post on the changepoint package, I concluded with a brief example of time series decomposition with the “decompose” command. After further reading, I discovered the “stl” command, which to me appears a superior method. STL stands for “Seasonal Decomposition of Time Series by LOESS”. By decomposition, we m...
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Are you ready for some Football? (No not soccer)
With two weeks of NFL football under our belts, it is time to start peaking under the proverbial hood at some of the statistics. What better way than with R? If you want the best stats out there, I recommend the website http://www.advancednflstats.com/ . In order to understand the variables you will need to spend some time looking at th...
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