1555 search results for "regression"

Data Exploration – Gold vs Gold Mining Stocks

February 12, 2012
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Data Exploration – Gold vs Gold Mining Stocks

I have been looking into time series analysis with R.  I'm still ramping up the learning curve as I am very accustomed to SAS/ETS.  With ETS, everything is in a couple of procedures, I know where and how to get things done.  In R, things...

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R for Quants, Part I.A

February 12, 2012
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R for Quants, Part I.A

I’m teaching an R workshop for the Baruch MFE program. This is the first installment of the workshop and focuses on …Continue reading »

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Machine Learning Examples in R

February 12, 2012
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Machine Learning Examples in R

This is a post that has been a long time in the making. Following on from the excellent Stanford Machine Learning Course I have made examples of the main algorithms covered in R.We have Linear RegressionFollowed by Neural NetworksAnd Support ...

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"R": Predicting a Test Set (Gasoline)

February 9, 2012
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"R": Predicting a Test Set (Gasoline)

> data(gasoline)> #60 spectra of gasoline (octane is the constituent) > #We divide the whole Set into a Train Set and a Test Set.> gasTrain<-gasoline> gasTest<-gasoline> #Let´s develop the PLSR with the Tain Set ...

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GARCH estimation using maximum likelihood

February 9, 2012
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In my previous post I presented my findings from my finance project under the guidance of Dr Susan Thomas. The results in my paper suggested that there are macroeconomic variables, particularly the INR/USD exchange rates, that help us understand the dynamics of stock returns. Although the results that I obtained were significant at 5%...

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Example 9.20: visualizing Simpson’s paradox

February 7, 2012
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Example 9.20: visualizing Simpson’s paradox

Simpson's paradox is always amazing to explain to students. What's bad for one group, and bad for another group is good for everyone, if you just collapse over the grouping variable. Unlike many mathematical paradoxes, this arises in a number of real...

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Workshop on Mixed and Multilevel Modelling with R in Toronto

February 7, 2012
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Summer Program In Data Analysis (SPIDA): May 24th – June 1st, 2012 In its thirteenth season this year, ISR’s Summer Program in Data Analysis focuses on linear models, beginning with “standard” regression through generalized linear models, and extending to mixed or multilevel models, linear and non-linear and generalized, which incorporate two or more hierarchical levels of data or longitudinal...

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General Bayesian estimation using MHadaptive

February 6, 2012
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General Bayesian estimation using MHadaptive

If you can write the likelihood function for your model, MHadaptive will take care of the rest (ie. all that MCMC business). I wrote this R package to simplify the estimation of posterior distributions of arbitrary models. Here’s how it works: 1) Define your model (ie the likelihood * prior). In this example, lets build

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Comparing correlations: independent and dependent (overlapping or non-overlapping)

February 5, 2012
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Comparing correlations: independent and dependent (overlapping or non-overlapping)

In Chapter 6 (correlation and covariance) I consider how to construct a confidence interval (CI) for the difference between two independent correlations.  The standard approach uses the Fisher z transformation to deal with boundary effects (the squashing of the distribution and increasing asymmetry as r approaches -1 or 1). As zr is approximately normally distributed

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Multiple Factor Model – Building Fundamental Factors

February 4, 2012
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Multiple Factor Model – Building Fundamental Factors

This is the second post in the series about Multiple Factor Models. I will build on the code presented in the prior post, Multiple Factor Model – Fundamental Data, and I will show how to build Fundamental factors described in the CSFB Alpha Factor Framework. For details of the CSFB Alpha Factor Framework please read

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