1713 search results for "Excel"

Conditional Formatting Tables using R

September 28, 2013
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One thing that I had the opportunity to develop while working last year at Saint Paul Public Schools was figuring out a quick, easy, and painless way to do interactive report generation. When I arrived in the REA department at Saint Paul Public Schools, the report generation process was roughly as follows: 1. Do the analysis in SPSS...

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elliplot 1.1.0 package released

September 27, 2013
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elliplot 1.1.0 package released

I released R package elliplot version 1.1.0. This package contains ellipseplot and midpoints. It is to visualize a correlation between 2 sets of independent observation with common factors.  Details are … Continue reading →

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Working with intraday data

September 24, 2013
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When working with intraday data, analysts are often facing a large dataset problem. R is well equipped to deal with this but the standard approach has to be modified in some ways. Large dataset means different things to different people. I’m talking here about a dataset of less than 10 columns and 2 to 5

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Munkres’ Assignment Algorithm with RcppArmadillo

September 24, 2013
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Munkres’ Assignment Algorithm with RcppArmadillo

Munkres’ Assignment Algorithm (Munkres (1957), also known as hungarian algorithm) is a well known algorithm in Operations Research solving the problem to optimally assign N jobs to N workers. I needed to solve the Minimal Assignment Problem for a relabeling algorithm in MCMC sampling for finite mixture distributions, where I use a random permutation Gibbs sampler. For each sample...

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A few gotchas with R date-time classes

September 21, 2013
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Date and time handling is essential to many modelling and analysis exercises, in R and other languages used for scientific computing. Over the past few months I tackled the mapping of date-time concepts between R and the .NET framework as part of the w...

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Are you ready for some Football? (No not soccer)

September 20, 2013
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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.advancedn...

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Where’s the Magic? (EMD and SSA in R)

September 17, 2013
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Where’s the Magic? (EMD and SSA in R)

When I first heard of SSA (Singular Spectrum Analysis) and the EMD (Empirical Mode Decomposition) I though surely I’ve found a couple of magical methods for decomposing a time series into component parts (trend, various seasonalities, various cycles, noise). And … Continue reading →

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Who uses E-Bikes in Toronto? Fun with Recursive Partitioning Trees and Toronto Open Data

September 12, 2013
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Who uses E-Bikes in Toronto?  Fun with Recursive Partitioning Trees and Toronto Open Data

I found a fun survey released to the Toronto Open Data website that investigates the travel/commuting behaviour of Torontonians, but with a special focus on E-bikes.  When I opened up the file, I found various demographic information, in addition to a … Continue reading →

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Direction of Change Forecasting using a Dynamic Binary Model

September 12, 2013
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Direction of Change Forecasting using a Dynamic Binary Model

While it is generally accepted that the returns of financial assets are almost impossible to forecast with any degree of accuracy which would provide meaningful profit1 , there is evidence that the sign of the returns is much more forecastable. Theoretically, Christoffersen and Diebold (2006) have shown how the forecastability of the sign is related

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An animated peek into the workings of Bayesian Statistics

September 9, 2013
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An animated peek into the workings of Bayesian Statistics

One of the practical challenges of Bayesian statistics is being able to deal with all of the complex probability distributions involved. You begin with the likelihood function of interest, but once you combine it with the prior distributions of all the parameters, you end up with a complex posterior distribution that you need to characterize. Since you usually can't...

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