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<p>Dear all,</p>
<p>On Thursday (14 March) at 2pm in <span class="event-where">54 / 7035 (7B), we have an S3RI seminar from Peter Neal (Lancaster University) on
</span><span class="event-where"><span class="event-description">"</span></span><span class="event-where"><span class="event-description"><span class="event-description"><span class="event-description">Efficient model comparison techniques for models requiring
large scale data augmentation</span></span>". Details are given below.<br>
</span></span></p>
<p><span class="event-where"><span class="event-description"><span><span class="event-description">The seminar will also be available via a live web-cast at</span></span></span></span><br>
<a class="moz-txt-link-freetext" href="https://coursecast.soton.ac.uk/Panopto/Pages/Viewer.aspx?id=c543bb6f-fa6a-4798-b7b2-aa0d008a1652">https://coursecast.soton.ac.uk/Panopto/Pages/Viewer.aspx?id=c543bb6f-fa6a-4798-b7b2-aa0d008a1652</a><br>
</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></p>
<p><span class="event-where"><span class="event-description"><span>Helen</span></span></span></p>
<p><span class="event-description"><br>
</span></p>
<p><span class="event-description">Efficient model comparison techniques for models requiring large scale data augmentation
<br>
</span></p>
<p><span class="event-description">Peter Neal, Lancaster University <br>
</span></p>
<p><span class="event-description">Selecting between competing statistical models is a challenging problem especially when the competing models are non-nested. We offer a simple solution by devising an algorithm which combines MCMC and importance sampling to
obtain computationally efficient estimates of the marginal likelihood (model evidence) which can then be used to compare the models. The incorporation of a particle filter step into the algorithm allows the algorithm to be successfully applied to time series
data sets, where calculating the marginal likelihood is made more challenging by the presence of large amounts of missing data.</span></p>
<br>
<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://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftinyurl.com%2Fs3riseminar&data=01%7C01%7C%7Cd6a1e707c32349c6a49808d6a5fb4e0e%7C4a5378f929f44d3ebe89669d03ada9d8%7C1&sdata=aDYn6AC7RRyIrf633cxxJy3WvrE%2BAhctOgE2gfJhDQE%3D&reserved=0" originalsrc="https://tinyurl.com/s3riseminar" shash="ox1ymeZn4vI0ZR8HWeIAhTC08b3q2mVQQHY9MKEzPOeFyjlPI9F/HZF5rGbGSzWGThh815ucnNnc0puMFDX133C47apnxDoh6H6DR19cQAof7RQUbTvfOBszSnW2D64y+GgZEpmFk7N4XI40P+j79siX3i3Df/CbzdY/ijq7hho=">
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>
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