# 1268 search results for "LaTeX"

## Census Atlas Japan

September 14, 2013
By

The 2011 Census Open Atlas project has been put on hold recently as various other research projects have intervened - more on these soon. However, over the summer  Chris Brunsdon and I have taken a research trip to Ritsumeikan University (Japan) where we visited Keiji Yano and Tomoki Nakaya. As part of this trip I began developing...

Read more »

## Monty Hall (oh no, not again)

September 13, 2013
By
$A$

Quite frequently, someone on the internet discovers the Monty Hall paradox, and become so enthusiastic that it becomes urgent to publish an article – or a post – about it. The latest example can be http://www.bbc.co.uk/news/magazine-24045598. I won’t blame them, I did the same a few years ago (see http://freakonometrics.hypotheses.org/776, or http://freakonometrics.hypotheses.org/775, in French). My point today is that the...

Read more »

## Non-observable vs. observable heterogeneity factor

September 11, 2013
By
$X$

This morning, in the ACT2040 class (on non-life insurance), we’ve discussed the difference between observable and non-observable heterogeneity in ratemaking (from an economic perspective). To illustrate that point (we will spend more time, later on, discussing observable and non-observable risk factors), we looked at the following simple example. Let  denote the height of a person. Consider the following dataset >...

Read more »

## The Beta Prior, Likelihood, and Posterior

September 4, 2013
By

The Beta distribution (and more generally the Dirichlet) are probably my favorite distributions.  However, sometimes only limited information is available when trying set up the distribution.  For example maybe you only know the lowest likely value, the highest likely value and the median, as a measure of center.  That information is sufficient to construct a

Read more »

## Latent Variable Analysis with R: Getting Setup with lavaan

September 1, 2013
By

Getting Started with Structural Equation Modeling Part 1Getting Started with Structural Equation Modeling: Part 1 Introduction For the analyst familiar with linear regression fitting structural equation models can at first feel strange. In the R environment, fitting structural equation models involves learning new modeling syntax, new plotting...

Read more »

## Introducing ‘propagate’

August 31, 2013
By
$Introducing ‘propagate’$

With this post, I want to introduce the new ‘propagate’ package on CRAN. It has one single purpose: propagation of uncertainties (“error propagation”). There is already one package on CRAN available for this task, named ‘metRology’ (http://cran.r-project.org/web/packages/metRology/index.html). ‘propagate’ has some additional functionality that some may find useful. The most important functions are: * propagate: A

Read more »

## Encouraging citation of software – introducing CITATION files

August 30, 2013
By

Summary: Put a plaintext file named CITATION in the root directory of your code, and put information in it about how to cite your software. Go on, do it now – it’ll only take two minutes! Software is very important in science – but good software takes time and effort that could be used to do

Read more »

## ECVP tutorial on classification images

August 30, 2013
By

The slides for my ECVP tutorial on classification images are available here. Try this alternative version if the equations look funny. (image from Mineault et al. 2009) The slides are in HTML and contain some interactive elements. They’re the result of experimenting with R Markdown, D3 and pandoc. You write the slides in R Markdown,

Read more »

## predictNLS (Part 2, Taylor approximation): confidence intervals for ‘nls’ models

August 26, 2013
By
$predictNLS (Part 2, Taylor approximation): confidence intervals for ‘nls’ models$

Initial Remark: Reload this page if formulas don’t display well! As promised, here is the second part on how to obtain confidence intervals for fitted values obtained from nonlinear regression via nls or nlsLM (package ‘minpack.lm’). I covered a Monte Carlo approach in http://rmazing.wordpress.com/2013/08/14/predictnls-part-1-monte-carlo-simulation-confidence-intervals-for-nls-models/, but here we will take a different approach: First- and second-order

Read more »

## From SVG to probability distributions [with R package]

August 25, 2013
By
$From SVG to probability distributions [with R package]$

Hey, To illustrate generally complex probability density functions on continuous spaces, researchers always use the same examples, for instance mixtures of Gaussian distributions or a banana shaped distribution defined on with density function: If we draw a sample from this distribution using MCMC we obtain a plot like this one: Clearly it doesn’t really look

Read more »

# Never miss an update! Subscribe to R-bloggers to receive e-mails with the latest R posts.(You will not see this message again.)

Click here to close (This popup will not appear again)