# 1028 search results for "latex"

## Lot of reports with a single click!

October 7, 2014
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Suppose you want to create a huge number of pdf files t

## The winds of Winter [Bayesian prediction]

October 6, 2014
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A surprising entry on arXiv this morning: Richard Vale (from Christchurch, NZ) has posted a paper about the characters appearing in the yet hypothetical next volume of George R.R. Martin’s Song of ice and fire series, The winds of Winter . Using the previous five books in the series

## A bit more fragmented

October 6, 2014
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Tweet This year election renders an even more fragmented legislative. The way political scientists measure this is by applying an algorithm to calculate the Effective Number of Parties, which is a measure that helps to go beyond the simple number of parties. A widely accepted algorithm was proposed by M. Laakso and R. Taagepera: , … Read More...

## What happens if we forget a trivial assumption ?

October 4, 2014
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$a$

Last week, @dmonniaux published an interesting post entitled l’erreur n’a rien d’original  on  his blog. He was asking the following question : let , and denote three real-valued coefficients, under which assumption on those three coefficients does has a real-valued root ? Everyone aswered , but no one mentioned that it is necessary to have a proper quadratic equation,...

## Cross Validation for Kernel Density Estimation

October 1, 2014
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$\mathbb{E}\left[\int [\widehat{f}_h(x)-f(x)]^2dx\right]$

In a post publihed in July, I mentioned the so called the Goldilocks principle, in the context of kermel density estimation, and bandwidth selection. The bandwith should not be too small (the variance would be too large) and it should not be too large (the bias would be too large). Another standard method to select the bandwith, as mentioned...

## Error propagation based on interval arithmetics

September 27, 2014
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$Error propagation based on interval arithmetics$

I added an interval function to my ‘propagate’ package (now on CRAN) that conducts error propagation based on interval arithmetics. It calculates the uncertainty of a model by using interval arithmetics based on (what I call) a “combinatorial sequence grid evaluation” approach, thereby avoiding the classical dependency problem that often inflates the result interval. This

## Multiple Tests, an Introduction

September 24, 2014
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$X_{i,t}$

Last week, a student asked me about multiple tests. More precisely, she ran an experience over – say – 20 weeks, with the same cohort of – say – 100 patients. An we observe some size=100 nb=20 set.seed(1) X=matrix(rnorm(size*nb),size,nb) (here, I just generate some fake data). I can visualize some trajectories, over the 20 weeks, library(RColorBrewer) cl1=brewer.pal(12,"Set3") cl2=brewer.pal(8,"Set2") cl=c(cl1,cl2)...

## a weird beamer feature…

September 23, 2014
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As I was preparing my slides for my third year undergraduate stat course, I got a weird error that got a search on the Web to unravel: which was related with a fragile environment but not directly the verbatim part: the reason for the bug was that the end{frame} command did not have a line

## momentify R package

September 19, 2014
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$momentify R package$

I presented today an arxived paper of my postdoc at the big success Young Bayesian Conference in Vienna. The big picture of the talk is simple: there are situations in Bayesian nonparametrics where you don’t know how to sample from the posterior distribution, but you can only compute posterior expectations (so-called marginal methods). So e.g. you cannot provide