1153 search results for "latex"

“A 99% TVaR is generally a 99.6% VaR”

August 29, 2015
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$\operatorname{VaR}_\alpha(F)=\inf\{x \in \mathbb{R}:F(x)\ge \alpha\}=F^{-1}(\alpha)$

Almost 6 years ago, I posted a brief comment on a sentence I found surprising, by that time, discovered in a report claiming that the expected shortfall  at the 99 % level corresponds quite closely to the  value-at-risk at a 99.6% level which was inspired by a remark in Swiss Experience report, expected shortfall  on a 99% confidence level […} corresponds to approximately 99.6% to...

Bio7 2.3 Released!

August 28, 2015
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28.08.2015 As a result of the useR conference 2015 with fantastic workshops and presentations where I also presented my software I released a new version of Bio7 with many improvements and new features inspired by the R conference and important for the next ImageJ conference 2015 where I will give a Bio7 workshop. For this

How to use lists in R

August 25, 2015
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In the (http://rforpublichealth.blogspot.com/2015/03/basics-of-lists.html), I went over the basics of lists, including constructing, manipulating, and converting lists to other classes. Knowing the basics, in this post, we'll use the **apply()** functions to see just how powerful working with lists can be. I've done two posts on apply for dataframes and matrics, (http://rforpublichealth.blogspot.com/2012/09/the-infamous-apply-function.html) and (http://rforpublichealth.blogspot.com/2013/10/loops-revisited-how-to-rethink-macros.html), so give those a...

Kickin’ it with elastic net regression

With the kind of data that I usually work with, overfitting regression models can be a huge problem if I'm not careful. Ridge regression is a really effective technique for thwarting overfitting. It does this by penalizing the L2 norm… Continue reading →

Bivariate Linear Regression

August 13, 2015
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Regression is one of the – maybe even the single most important fundamental tool for statistical analysis in quite a large number of research areas. It forms the basis of many of the fancy statistical methods currently en vogue in the social sciences. Multilevel analysis and structural equation modeling are perhaps the most widespread and

Moment conditions and Bayesian nonparametrics

August 5, 2015
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Luke Bornn, Neil Shephard, and Reza Solgi (all from Harvard) have arXived a pretty interesting paper on simulating targets on a zero measure set. Although it is not initially presented this way, but rather in non-parametric terms as moment conditions where θ is the parameter of the sampling distribution, constrained by the value of β. (Which

Producing a Control Chart in R – An Application in Analytical Chemistry

Introduction Many processes in chemistry, especially in synthesis, require attaining a certain target value for a property of interest.  For example, when synthesizing drug capsules that contain a medicine, a chemist has to ensure that the concentration of the medicine meets a target value.  If the concentration is too high or too low, then the patient

Goals for the New R Consortium

July 28, 2015
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by Bob Muenchen The recently-created R Consortium consists of companies that are deeply involved in R such as RStudio, Microsoft/Revolution Analytics, Tibco, and others. The Consortium’s goals include advancing R’s worldwide promotion and support, encouraging user adoption, and improving documentation … Continue reading →

Modelling Occurence of Events, with some Exposure

July 28, 2015
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$Y_i^\star$

This afternoon, an interesting point was raised, and I wanted to get back on it (since I did publish a post on that same topic a long time ago). How can we adapt a logistic regression when all the observations do not have the same exposure. Here the model is the following: , the occurence of an event  on the period ...

Why I use Panel/Multilevel Methods

July 24, 2015
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$Why I use Panel/Multilevel Methods$

I don’t understand why any researcher would choose not to use panel/multilevel methods on panel/hierarchical data. Let’s take the following linear regression as an example: , where is a random effect for the i-th group. A pooled OLS regression model for the above is unbiased and consistent. However, it will be inefficient, unless for all