Posts Tagged ‘ statistics ’

Florid’AISTATS

August 30, 2016
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Florid’AISTATS

The next AISTATS conference is taking place in Florida, Fort Lauderdale, on April 20-22. (The website keeps the same address one conference after another, which means all my links to the AISTATS 2016 conference in Cadiz are no longer valid. And that the above sunset from Florida is named… cadiz.jpg!) The deadline for paper submission […]

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The R community is awesome (and fast)

August 30, 2016
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Recently I whined/whinged or generally complained about a few sharp edges in some powerful R systems. In each case I was treated very politely, listened to, and actually got fixes back in a very short timeframe from volunteers. That is really great and probably one of the many reasons R is a great ecosystem. Please … Continue reading The R community is awesome (and fast)

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Variable pruning is NP hard

August 28, 2016
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I am working on some practical articles on variable selection, especially in the context of step-wise linear regression and logistic regression. One thing I noticed while preparing some examples is that summaries such as model quality (especially out of sample quality) and variable significances are not quite as simple as one would hope (they in … Continue reading Variable pruning is NP hard

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vtreat 0.5.27 released on CRAN

August 19, 2016
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Win-Vector LLC, Nina Zumel and I are pleased to announce that ‘vtreat’ version 0.5.27 has been released on CRAN. vtreat is a data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. (from the package documentation) Very roughly vtreat accepts an arbitrary “from the wild” data frame (with different column types, … Continue reading vtreat 0.5.27 released on CRAN

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Trading strategy: Making the most of the out of sample data

August 19, 2016
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Trading strategy: Making the most of the out of sample data

When testing trading strategies a common approach is to divide the initial data set into in sample data: the part of the data designed to calibrate the model and out of sample data: the part of the data used to validate the calibration and ensure that the performance created in sample will be reflected in the […]

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My criticism of R numeric summary

August 18, 2016
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My criticism of R numeric summary

My criticism of R‘s numeric summary() method is: it is unfaithful to numeric arguments (due to bad default behavior) and frankly it should be considered unreliable. It is likely the way it is for historic and compatibility reasons, but in my opinion it does not currently represent a desirable set of tradeoffs. summary() likely represents … Continue reading My criticism of R numeric summary

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The Win-Vector parallel computing in R series

August 16, 2016
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With our recent publication of “Can you nest parallel operations in R?” we now have a nice series of “how to speed up statistical computations in R” that moves from application, to larger/cloud application, and then to details. For your convenience here they are in order: A gentle introduction to parallel computing in R Running … Continue reading The Win-Vector parallel computing in R series

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Stop saying confidence intervals are "better" than p values

July 29, 2016
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Stop saying confidence intervals are "better" than p values

One of the common tropes one hears from advocates of confidence intervals is that they are superior, or should be preferred, to p values. In our paper "The Fallacy of Placing Confidence in Confidence Intervals", we outlined a number of interpretation p...

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Round values while preserve their rounded sum in R

July 28, 2016
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After an embarrassing teleconference in which I presented a series of percentages that did not sum to 100 (as they should have), I found some R code on stackoverflow.com to help me to avoid this in the future. In general, the sum of rounded numbers (e.g., using the base::round function) is not the same as … Continue reading Round values while preserve their rounded sum in R →

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Bayesian Essentials with R [book review]

July 27, 2016
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Bayesian Essentials with R [book review]

[A review of Bayesian Essentials that appeared in Technometrics two weeks ago, with the first author being rechristened Jean-Michael!] “Overall this book is a very helpful and useful introduction to Bayesian methods of data analysis. I found the use of R, the code in the book, and the companion R package, bayess, to be helpful […]

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