<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
</head>
<body text="#000000" bgcolor="#FFFFFF">
<p>Dear all,</p>
<p>On Thursday (6 December) at 2pm in <span class="event-where">54
/ 7035 (7B), we have an S3RI seminar from </span><span
class="event-where">Mario Cortina Borja (University College
London) on </span><span class="event-where"><span
class="event-description">"</span></span><span
class="event-where"><span class="event-description"><span
class="event-description">Bayesian inference for bivariate
copulas with additive models for dependence, marginal
location, scale and shape: an application in paediatric
ophthalmology</span>". Details are given below.<br>
</span></span></p>
<p><span class="event-where"><span class="event-description"><span><span
class="event-description">The talk will be followed by tea
and cake in the staff reading room on level 4 of building
54. </span></span></span></span></p>
<p><span class="event-where"><span class="event-description"><span><span
class="event-description">All are welcome!</span></span></span></span></p>
<p><span class="event-where"><span class="event-description"><span>Best
wishes,</span></span></span><span class="event-where"><span
class="event-description"><span><br>
Helen</span></span></span></p>
<p>Bayesian inference for bivariate copulas with additive models for
dependence, marginal location, scale and shape: an application in
paediatric ophthalmology <br>
</p>
<p>Mario Cortina Borja, University College London <br>
</p>
<p>Motivated by data on visual acuity from a large sample of
children aged between 3 and 8 years, we propose bivariate copula
models with dependence parameters, and sinh-arcsinh marginal
densities with location, scale and shape parameters that depend on
a covariate through additive models. We perform inference about
the unknown quantities of our model in the Bayesian framework
using a Markov chain Monte Carlo algorithm. We apply our model to
paediatric ophthalmic data to gain new insights about the
processes which cause changes in visual acuity with respect to
age, including the age-related nature of the copula dependence
parameter. We analyse predictive distributions to identify
children with unusual sight characteristics, distinguishing those
who are bivariate, but not univariate outliers. In this way we
provide an innovative tool that enables clinicians to identify
children with unusual sight who may otherwise be missed. <br>
</p>
<p>Work in collaboration with Julian Stander and Luciana Dalla Valle
(Plymouth), Brunero Liseo (Rome), Charlotte Taglioni (Padua), and
Angie Wade (UCL). </p>
<span class="event-where"><span class="event-description"><span><span
class="event-description"><span> <span
class="event-description"> </span><span
class="event-description"><span
class="event-description">For the current schedule of
S3RI seminars, see <a class="moz-txt-link-freetext"
href="https://tinyurl.com/s3riseminar">https://tinyurl.com/s3riseminar</a>
</span></span></span></span></span></span></span><br>
<p><span class="event-where"><span class="event-description"><span><span
class="event-description"></span></span></span></span></p>
</body>
</html>