Posts Tagged ‘ R ’

Early bird registration for R in Insurance closes 30 May

May 24, 2016
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Hurry! The early bird registration offer for the 4th R in Insurance conference, 11 July 2016, at Cass Business School closes 30 May.This one-day conference will focus once more on applications in insurance and actuarial science that use R, the lingua f...

Principal Components Regression, Pt. 2: Y-Aware Methods

May 23, 2016
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In our previous note, we discussed some problems that can arise when using standard principal components analysis (specifically, principal components regression) to model the relationship between independent (x) and dependent (y) variables. In this note, we present some dimensionality reduction techniques that alleviate some of those problems, in particular what we call Y-Aware Principal Components … Continue reading Principal Components Regression, Pt. 2: Y-Aware Methods

occupancy rules

May 22, 2016
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$occupancy rules$

While the last riddle on The Riddler was rather anticlimactic, namely to find the mean of the number Y of empty bins in a uniform multinomial with n bins and m draws, with solution [which still has a link with e in that the fraction of empty bins converges to e⁻¹ when n=m], this led […]

BCEA 2.2-3 is out

May 22, 2016
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I think the newest release of BCEA, our R package to standardise and post-process the output of a health economic model, is now available from CRAN \$-\$ in fact, the source code is also available here. The package is rather stable, so the...

Simulating a Weibull conditional on time-to-event is greater than a given time

May 20, 2016
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Recently, I had to simulate a time-to-event of subjects who have been on a study, are still ongoing at the time of a data cut, but who are still at risk of an event (e.g. progressive disease, cardiac event, death). This requires the simulation of a con...

ABC random forests for Bayesian parameter inference

May 19, 2016
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Before leaving Helsinki, we arXived [from the Air France lounge!] the paper Jean-Michel presented on Monday at ABCruise in Helsinki. This paper summarises the experiments Louis conducted over the past months to assess the great performances of a random forest regression approach to ABC parameter inference. Thus validating in this experimental sense the use of […]

Using MCMC output to efficiently estimate Bayes factors

May 18, 2016
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$Using MCMC output to efficiently estimate Bayes factors$

As I was checking for software to answer a query on X validated about generic Bayes factor derivation, I came across an R software called BayesFactor, which only applies in regression settings and relies on the Savage-Dickey representation of the Bayes factor when the null hypothesis writes as θ=θ⁰ (and possibly additional nuisance parameters with […]

May 17, 2016
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Occasionally readers ask about the exams that I set in my graduate econometrics courses.The elective graduate econometrics course that I taught this past semester was one titled "Themes in Econometrics". The topics that are covered vary from year to ye...

Principal Components Regression, Pt.1: The Standard Method

May 17, 2016
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In this note, we discuss principal components regression and some of the issues with it: The need for scaling. The need for pruning. The lack of “y-awareness” of the standard dimensionality reduction step. The purpose of this article is to set the stage for presenting dimensionality reduction techniques appropriate for predictive modeling, such as y-aware … Continue reading Principal Components Regression, Pt.1: The Standard Method

Sharp-R May Update

May 16, 2016
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Another update has been made to Sharp-R bringing it to version 1.2. The main changes are, Multiple function files. Built in standard functions. Changes to the XML function files. Bug fixes. We have increased the number of function files that can loaded...