I am looking for a new car. So when I saw there was an update on vehicles in Statistics Netherlands I just had to go and look at the data. So, I learned the brown is getting more popular, often the number of cars from a certain construction year is ... [Read more...]

After last week's post bubble sort tuning I got an email from Berend Hasselman noting that my 'best' function did not protect against cases n [Read more...]

I was reading Paul Hiemsta's blogpost on Much more efficient bubble sort in R using the Rcpp and inline packages, went back to his first post  Bubble sort implemented in pure R and thought, surely we can do it better in pure R. So I... [Read more...]

Preparing and reshaping data is the ever continuing task of a data analyst. Luckily we have many tools for it. The default tool in R would be reshape(), although this is so user friendly that a reshape package has been added too. I try to use reshape()... [Read more...]

After last post's setting up for a simulation, it is now time to look how the models compare. To my disappointment with my simple simulations of assessors behavior the gain is minimal. Unfortunately, the simulation took much more time than I ... [Read more...]

I recently made three posts regarding analysis of ordinal data. A post looking at all methods I could find in R, a post with an additional method and a post using JAGS. Common in all three was using the cheese data, a data set where... [Read more...]

I am continuing in Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Lifeby Steven Strogatz. To get a feeling on it, I was building a group of things which have only a minute influence on each other are able to synchronize thei... [Read more...]

I am listening to the audiobook Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Lifeby Steven Strogatz which I got from Audible. Obviously a mathematical book is not ideal to listen to, but lacking illustrations I can ma... [Read more...]

The past two weeks I made a post regarding analyzing ordinal data with R and JAGS. The calculations in the second part made me realize I could actually get top two box intervals out of R. This demonstrated here. For that I needed the inv... [Read more...]

Last week is had a look at the standard R routines for estimating models for ordinal data. This week, I want to have a look at JAGS for examining the same data. To be honest, most of it is taking an example (inhaler) and removing code. To my surpr... [Read more...]

I expect to be getting some ordinal data, from 5 or 9 point rating scales, pretty soon, so I am having a look ahead how to treat those. Often ANOVA is used, even though it is well known not to be ideal fro a statistical point of view, so that is the ... [Read more...]

I looked before at triangle tests and at sequential testing in triangle tests (blog entry). In the latter post it was demonstrated that a sequential test is possible, without costs in desired error of the first kind. The latter because t... [Read more...]

I wanted to know a bit more about the number of people suffering from Alzheimer. It has been getting more attention and it runs in my family. From CBS (Statistics Netherlands) I pulled the data regarding the number of people dying from it. I am af... [Read more...]

In the Netherlands we have Natural Gas. Unfortunately winning this gas seems to cause some quakes. As quakes go, they are not strong. However, our buildings are not made to resist quakes, before 1986 they were unheard of, so there is some damage. It is now predicted they could get stronger ... [Read more...]

After last week's post it was commented that strucchange and segmented would be more suitable for my purpose. I had a look at both. Strucchange can find a jump in a time series, which was what I was looking for. In contrast segmented is more suitable f... [Read more...]

The other day I saw a plot with some data with a clear jump in it. So I wondered if it were possible to determine the position of that jump. Data with a jump is easy enough made:library(ggplot2)n [Read more...]

That is what I read the other day. For calculation of descriptive statistics, values below the LLOQ (lower limit of quantification)  were set to.... Then I wondered, wasn't there a trick in JAGS to incorporate the presence of missing data while es... [Read more...]

I am playing around with Eurostat data and ggplot2 a bit more. As I progress it seems the plotting gets more easy, the data pre-processing a bit more simple and the surprises on the data stay.Eurostat dataThe data used are fish_fleet (number of ships) and fish_pr (production=... [Read more...]

Last week on the radio I heard a story of southern Europeans and Irish looking for better times in northern Europe. I heard the tale of an Italian academic who left Italy to end up waiting tables in an Italian restaurant in the Netherlands. Obviously t... [Read more...]

It is well known the binomial test never has an error of exactly 5%. You aim for at most 5%, calculate the number correct to get there and end up with an error of e.g 2%. This is a shame but there is no solution. However, it is also an opportunity; the... [Read more...]