Basic “Hello World” baposter Poster.

Finished my second poster using the baposter class in LaTeX. As with the first time, it took a little while to set up the poster style. In the end I found it a lot easier to strip down one of the examples on the baposter website. This gave me a really simple poster….

I then worked on building this up to get precisely the poster style I wanted. I found it a lot easier to experiment with a basic template than adapt the more complicated examples around on the web.

Below is the tex code for this poster. I have also put in comments for each of the options available. Hopefully you can run this code fairly easily to get the same poster, and then  develop your own. There are two things you will need in the directory where you save the .tex file below to replicate the poster… 1) the baposter.cls file from the Brian Amberg’s baposter website 2) the rolling-stones.pdf file (get it here). Let me know in the comments if you have any problems or find any other options?

% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
%
% Class Options (see http://www.brian-amberg.de/uni/poster/baposter/baposter_guide.pdf for more details)
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
% a0paper               % paper size (choose one)
% a1paper               %
% a2paper               %
% a3paper               %
% a4paper               %
% archE                 %
%
% paperwidth = length   % alternative to paper size eg paperwidth=100cm
% paperheight = length  %
%
% landscape             % paper orientation (choose one)
% portrait              %
%
% margin = length       % give length e.g. margin=2cm
%
% fontscale = number    % font size
%
% showframe             % frame for debugging
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
\documentclass[a0paper,landscape]{baposter}
\usepackage{graphicx} %to insert pictures
\usepackage{color} %to set colors
\usepackage{helvet} %to use helvet font
\renewcommand{\familydefault}{\sfdefault} %set default font to sans-serif for entire document.

\begin{document}
\begin{poster}{
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
%
% Poster Environment Options (see http://www.brian-amberg.de/uni/poster/baposter/baposter_guide.pdf for more details)
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
% grid = true               % grid for helping design  (choose one)
% grid = false              %
%
% columns = number          % number of columns (default 4 in landscape and 3 in portrait format, maximum number is 6)
%
% colspacing = length       % space betweeen columns e.g. colspacing=0.5cm
%
% headerheight = length     % height of poster header (not boxes in poster), default value is 0.1\textheight
%
% background = plain        % background type set as bgColorOne
% background = shade-lr     % background type shades from bgColorOne to bgColorTwo
% background = shade-tb     % background type shades from bgColorOne to bgColorTwo
% background = user         % background from user picture, (set as \background{...})
% background = none         % no background
%
% bgColorOne = color name   % backgound color 1
% bgColorTWO = color name   % backgound color 2 (used for shading)
%
% eyecatcher = true         % eyecatcher image (choose one)
% eyecatcher = false        %
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
grid=false,
columns=4,
colspacing=0.5cm,
headerheight=0.1\textheight,
background=plain,
bgColorOne=white,
bgColorTwo=red,
eyecatcher=false,
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
%
% Posterbox Environment Options (see http://www.brian-amberg.de/uni/poster/baposter/baposter_guide.pdf for more details)
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
% borderColor = color             % box border color
%
% headerColorOne = color          % box header color 1
% headerColorTwo = color          % box header color 2
%
% textborder = none               % lower box border type/shape (choose one)
% textborder = bars               %
% textborder = coils              %
% textborder = triangles          %
% textborder = rectangle          %
% textborder = rounded            %
% textborder = faded              %
% textborder = roundedsmall       %
% textborder = roundedleft        %
% textborder = roundedright       %
%
% headerborder = none             % upper box border type (choose one)
% headerborder = closed           %
% headerborder = open             %
%
% headershape = rectangle         % upper box border shape (choose one)
% headershape = small-rounded     %
% headershape = roundedright      %
% headershape = roundedleft       %
% headershape = rounded           %
%
% headershade = plain             % upper box shading type (choose one)
% headershade = shade-lr          % left to right
% headershade = shade-tb          % top to bottom
% headershade = shade-tb-inverse  %
%
% boxshade = shade-lr             % lower box shading type (choose one)
% boxshade = shade-tb             %
% boxshade = plain                %
% boxshade = none                 %
%
% headerfont = font               % font type in box header
% headerFontColor = color         % font color in box header
%
% linewidth = length              % width of box border lines
%
% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %
borderColor=black,
headerColorOne=red,
headerColorTwo=red,
textborder=roundedsmall,
headerborder=closed,
headershape=roundedright,
headershade=plain,
boxshade=none,
headerfont=\sc,
headerFontColor=white,
linewidth=0.15cm
}
%%
%% POSTER HEADER
%%
% Eye Catcher Images to go left of your title.
{\includegraphics[height=0.1\textheight]{rolling-stones.pdf}} %will not show if put eyecatcher=false
% Title
{Poster Title}
% Author
{Author}
% Logo
{\includegraphics[height=0.1\textheight]{rolling-stones.pdf}}

%%
%% POSTER CONTENTS
%%
% BOX 1
\headerbox{Box 1}{name=box1,column=0,row=0}{
blah
}
% BOX 2
\headerbox{Box 2}{name=box2,column=0,below=box1}{
blah blah
}
% BOX 3
\headerbox{Box 3}{name=box3,column=1}{
blah blah blah
}
% BOX 4
\headerbox{Box 4}{name=box4,column=1,below=box3,span=2}{
blah blah blah, blah blah blah
}
% BOX 5
\headerbox{Box 5}{name=box5,column=2}{
blah blah
}
% BOX 6
\headerbox{Box 6}{name=box6,column=3}{
blah blah blah blah
}
\end{poster}
\end{document}

A comparison of official population projections with Bayesian time series forecasts for England and Wales

A paper based on my some work I did with colleagues in the ESRC Centre for Population Change was published in the the Population Trends. We fitted a range of time series models (including some volatility models) to population change data for England and Wales, calculated the posterior model probabilities and then projected from the model averaged posterior predictive distributions. We found our volatility models were heavily supported. Our median matches very closely the Office of National Statistics mid scenario. It’s a tad surprising that projections based on forecasts of a single annual growth rate per year give a similar forecast to the ONS cohort component projection which are based on hundreds of future age-sex specific fertility, mortality and net migration rates. The ONS do not provide any form probabilistic uncertainty, instead the give a expert based high and low scenario, which roughly calibrated to our 50% prediction interval in 2033. I ran all the models in BUGS and did the fan chart plots in R.

Publication Details:

Abel, G.J., Bijak, J. and Raymer J. (2010). A comparison of official population projections with Bayesian time series forecasts for England and Wales. Population Trends, 141, 95–114.

We compare official population projections with Bayesian time series forecasts for England and Wales. The Bayesian approach allows the integration of uncertainty in the data, models and model parameters in a coherent and consistent manner. Bayesian methodology for time-series forecasting is introduced, including autoregressive (AR) and stochastic volatility (SV) models. These models are then fitted to a historical time series of data from 1841 to 2007 and used to predict future population totals to 2033. These results are compared to the most recent projections produced by the Office for National Statistics. Sensitivity analyses are then performed to test the effect of changes in the prior uncertainty for a single parameter. Finally, in-sample forecasts are compared with actual population and previous official projections. The article ends with some conclusions and recommendations for future work.

Estimation of international migration flow tables in Europe

A paper based on my Ph.D. has been published in the Journal of the Royal Statistical Society: Series A (Statistics in Society). It is essentially a boiled down version of my Ph.D. thesis without some of the earlier chapters. The idea was to come up with some comparable estimates of bilateral migration flows, which currently do not exist. I used some modern optimisation methods to harmonise existing migration flow data, and then the EM algorithm to derive some model based imputations where there is no existing flow data. Below are the results I got for the EU15, 2002-2006 (use the tabs at the bottom to view different years).


If you want to download the data, go to the Google spreadsheet here.

Publication Details:

Abel, G. J (2010) Estimation of international migration flow tables in Europe. Journal of the Royal Statistical Society: Series A (Statistics in Society), Volume 173 Issue 4, Pages 797–825.

A methodology is developed to estimate comparable international migration flows between a set of countries. International migration flow data may be missing, reported by the sending country, reported by the receiving country or reported by both the sending and the receiving countries. For the last situation, reported counts rarely match owing to differences in definitions and data collection systems. We report counts harmonized by using correction factors estimated from a constrained optimization procedure. Factors are applied to scale data that are known to be of a reliable standard, creating an incomplete migration flow table of harmonized values. Cells for which no reliable reported flows exist are then estimated from a negative binomial regression model fitted by using an expectation–maximization (EM) type of algorithm. Covariate information for this model is drawn from international migration theory. Finally, measures of precision for all missing cell estimates are derived by using the supplemented EM algorithm. Recent data on international migration between countries in Europe are used to illustrate the methodology. The results represent a complete table of comparable flows which can be used by regional policy makers and social scientists to understand population behaviour and change better.

International Migration Flow Table Estimation

International migration flow data is a messy topic. No single pair of countries defines migration in the same way. Even if the did they most likely measure if differently. This causes some big headaches to anyone who wants to create any inference about migration levels, directions, policy implications or the cause and consequences of people’s movements at a cross national level. During my Ph.D. I worked on methods for estimating comparable international migration flows across multiple European countries.

I identified two fundamental data problems: inconsistency (countries with conflicting reports on the number of people moving between them) of and incompleteness (countries not providing any data). I applied both mathematical and statistical methods to create comparable set of international migration flow estimates. For more details see my Ph.D. dissertation (which is online, see the link below). It contains most of the R/S-Plus code to conduct the estimation in the Appendix. Note, there is also a published paper based on my Ph.D. (abstract and links here). I created a TeX template for the University of Southampton School of Social Sciences here.

Publication Details:

Abel, G. J. (2009). International Migration Flow Table Estimation. University of Southampton, Division of Social Statistics, Doctoral Thesis.

Sequential Line Plots in R

I was trying to create some sequential plots today in R to analyse some MCMC simulations. I found the par(ask=TRUE) command very useful for looking at iterations of individual parameter values. Setting the ask graphical parameter to TRUE (before a for loop) allows you to update plots by clicking on the plotting device (in windows). Here is some example code to show how par(ask=TRUE) works.

xx <- rnorm(1000)
xx <- matrix(xx,10,100)
par(ask = TRUE)
plot(xx[1,], type="n", ylim=range(xx), ylab="")
for(i in 1:10){
   plot(xx[i,], ylim=range(xx), ylab="", type="l")
}

This will give the following output after each click:
ask1

If you want to keep previous plotted lines on the plot you can adapt the for loop in such a manner:

par(ask=TRUE)
plot(xx[1,], type="n", ylim=range(xx), ylab="")
for(i in 1:10){
   plot(xx[1,], ylim=range(xx), ylab="", type="l")
   for(j in 1:i){
      lines(xx[j,])
   }
}

This will give the following output after each click:
ask2

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