1695 search results for "Excel"

Storing package data in custom environments

Storing package data in custom environments If you do R package development, sometimes you want to be able to store variables specific to your package, without cluttering up the users workspace. One way to do this is by modifying the global options. This is done by packages grDevices and parallel. Sometimes this doesn't seem to work quite right (see this...

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Tim Hortons Density

Tim Hortons Density

Tim Hortons Density Inspired by this post, I wanted to examine the locations and density of Tim Hortons restaurants in Canada. Using Stats Canada data, each census tract is queried on Foursquare for Tims locations. Setup options(stringsAsFactors = F) require(timmysDensity) require(plyr) require(maps) require(ggplot2) require(geosphere) Statistics Canada Census Data The actual Statistics Canada data at the dissemination block level can be downloaded from here. You will want to...

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On the growth of R and Python for data science

December 6, 2013
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On the growth of R and Python for data science

A recent article by Matt Asay claims that "Python is displacing R as the language for data science". Python has certainly made some great strides in recent years, evolving beyond a data processing tool (an area where Python excels) to a data analysis tool. The Pandas project, in particular, has greatly expanded Python's ability to handle statistical data sets...

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Averaged Input Assumptions and Momentum

December 4, 2013
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Averaged Input Assumptions and Momentum

Today I want to share another interesting idea contributed by Pierre Chretien. Pierre suggested using Averaged Input Assumptions and Momentum to create reasonably quiet strategy. The averaging techniques are used to avoid over-fitting any particular frequency. To create Averaged Input Assumptions we combine returns over different look-back periods, giving more weight to the recent returns,

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R – Analyze any data frame in Saiku

December 4, 2013
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R – Analyze any data frame in Saiku

In my previous article I have shown how R can be used to analyze PostgreSQL tables in Saiku using dynamically generated OLAP cubes. Today I will show you how you can analyze any R data frame in Saiku. WIth Saiku you can easily create excel-like pivot t...

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Maximizing Return from Every Item in the Marketing Research Questionnaire

December 3, 2013
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Maximizing Return from Every Item in the Marketing Research Questionnaire

Consumers will not complete long questionnaires, so marketing research must get the most it can from every item.  In this post, we look into the toolbox of R packages and search for statistical models that enable us to learn a great deal about eac...

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24 Days of R: Day 1

December 1, 2013
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24 Days of R: Day 1

Last year, the good people at is.R() spent December publishing an R advent calendar. This meant that for 24 days, every day, there was an interesting post featuring analysis and some excellent visualizations in R. I think it's an interesting (if very challenging) exercise and I'm going to try to do it myself this year.

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JAGS model Fe concentration in rainwater including values below detection level

December 1, 2013
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JAGS model Fe concentration in rainwater including values below detection level

In my previous post I ignored the fact that some data are below the detection level. I would not know how to handle those in a mixed model from lme4 or nlme. However, JAGS can handle these values. Next to that I kept the usual independent variables, su...

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More Explorations with catR

December 1, 2013
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More Explorations with catR

# For the purposes of simulating computerized adaptive tests# the R package catR is unparallelled. # catR is an excellent tool for students who are curious about# how a computerized adaptive test might work. It is also useful# for testing companie...

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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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