Anúncios · Seminário de Investigação em Probabilidades e Estatística I
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/sumarios/announcement
Anúncios · Seminário de Investigação em Probabilidades e Estatística I
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Research Seminar in Probability and Statistics I  #5
<p>Binary autoregressive geometric modelling in a DNA
context</p><p>Sónia Gouveia (<em>Institute
of Electronics and Informatics Engineering and Centre for R&D in
Mathematics and Applications, University of Aveiro, Portugal</em>)</p>
<p><b>November </b>22<b> </b>(Tue.), <b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST,
Av. Rovisco Pais, 1049001 Lisboa)</p><p>Symbolic sequences occur in many contexts and can be characterized
e.g. by integervalued intersymbol distances or binaryvalued indicator
sequences. The analysis of these numerical sequences often sheds light
on the properties of the original symbolic sequences. This talk
introduces new statistical tools to explore the autocorrelation
structure in indicator sequences and to evaluate its impact on the
probability distribution of intersymbol distances. The methods are
illustrated with data extracted from mitochondrial DNA sequences.</p><p>This
is a joint work with Manuel Scotto (IST, Lisbon, Portugal), Christian
Weiss (Helmut Schmidt University, Hamburg, Germany) and Paulo Ferreira
(DETI, IEETA, Aveiro, Portugal).</p><p><a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a></p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi5
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi5#1689399616107527
Anúncios
Wed, 16 Nov 2016 19:39:58 +0000

Research Seminar in Probability and Statistics I  #4
<p>On
the peaksoverthreshold method in extreme value theory</p>Laurens de Haan<b> </b>(Erasmus University Rotterdam and Centro de Estatística e Aplicações da UL)
<p><b>November </b>8<b> </b>(Tue.), <b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST,
Av. Rovisco Pais, 1049001 Lisboa)</p>
<p> </p>
<p>The origin, the development and the use of the peaksoverthreshold
method (in particular in higherdimensional spaces) will be discussed as well
as some issues that need clarification.</p>
<p> </p>
<p><a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a></p>
<p> </p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi4
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi4#1689399616103001
Anúncios
Tue, 25 Oct 2016 18:29:07 +0100

Research Seminar in Probability and Statistics I  #3
<p><b>Spatial and SpatioTemporal Nonlinear Time Series</b></p>
<p><b>Wolfgang Schmid </b>(European University, Frankfurt (Oder), Germany)</p>
<p> </p><p><b>October </b>25<b>
</b>(Tue.), <b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST, Av. Rovisco
Pais, 1049001 Lisboa)</p>
<p> </p><p>In this talk we present a new spatial
model that incorporates heteroscedastic variance depending on neighboring
locations. The proposed process is regarded as the spatial equivalent to the
temporal autoregressive conditional heteroscedasticity (ARCH) model. We show
additionally how the introduced spatial ARCH model can be used in
spatiotemporal settings. In contrast to the temporal ARCH model, in which the
distribution is known given the full information set of the prior periods, the
distribution is not straightforward in the spatial and spatiotemporal setting.
However, it is possible to estimate the parameters of the model using the
maximumlikelihood approach. Via Monte Carlo simulations, we demonstrate the
performance of the estimator for a specific spatial weighting matrix. Moreover,
we combine the known spatial autoregressive model with the spatial ARCH model
assuming heteroscedastic errors. Eventually, the proposed autoregressive
process is illustrated using an empirical example. Specifically, we model lung
cancer mortality in 3108 U.S. counties and compare the introduced model with
two benchmark approaches.</p>
<p>(joint work with Robert Gartho and
Philipp Otto)</p>
<p>.</p>
<p> </p>
<p><a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a></p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi3
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi3#1689399616099550
Anúncios
Tue, 11 Oct 2016 17:24:20 +0100

Research Seminar in Probability and Statistics I  #1
<p><b>An
ARLunbiased npchart</b></p>
<p><b>Manuel Cabral Morais </b>(DMIST; CEMAT)</p>
<p><b>September </b>27<b> </b>(Tue.),
<b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST, Av. Rovisco Pais,
1049001 Lisboa)</p>
<p>We usually
assume that counts of nonconforming items have a binomial distribution with
parameters (n,p), where n and p represent the sample size and the fraction
nonconforming, respectively. </p>
<p>The nonnegative,
discrete and usually skewed character and the target mean (np_0) of this
distribution may prevent the quality control engineer to deal with a chart to
monitor p with: a prespecified incontrol average run length (ARL), say
1/alpha; a positive lower control limit; the ability to control not only
increases but also decreases in p in a expedient fashion. Furthermore, as far
as we have investigated, the np and pcharts proposed in the Statistical
Process Control literature are ARLbiased, in the sense that they take longer,
in average, to detect some shifts in the fraction nonconforming than to trigger
a false alarm. </p>
<p>Having all
this in mind, this paper explores the notions of uniformly most powerful
unbiased tests with randomization probabilities to eliminate the bias of the
ARL function of the npchart and to bring its incontrol ARL exactly to
1/alpha.</p>
<p><a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a></p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi1
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi1#1689399616094036
Anúncios
Fri, 16 Sep 2016 15:59:15 +0100

Research Seminar in Probability and Statistics I  #6
<p>Modelling extremal
temporal dependence in stationary time series</p>
<p>Alexandra Ramos (<em>Faculdade
de Economia da Universidade do Porto</em><em>)</em></p>
<p> <b>December </b>13<b> </b>(Tue.), <b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST,
Av. Rovisco Pais, 1049001 Lisboa)
</p><p> Extreme value
theory concerns the statistical study of the extremal properties of random
processes. The most common problems treated by extreme value methods involve
modeling the tail of an unknown distribution function from a set of observed
data with the purpose of quantifying the frequency and severity of events more
extreme than any that have been observed previously. A fundamental issue in
applied multivariate extreme value (MEV) analysis is modelling dependence
within joint tail regions. In this seminar we suggest modelling joint tails of
the distribution of two consecutive pairs (X<sub>i</sub>;X<sub>i+1</sub>) of a
firstorder stationary Markov chain by a dependence model described in Ramos
and Ledford (2009). Applications of this modelling approach to real data are
then considered.
</p><p>Ramos and Ledford (2009). A new class of models for bivariate joint tails. J. R. Statist. Soc., B. 71. p. 219241.</p>
<p> <a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a>
</p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi6
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi6#1407924639376421
Anúncios
Fri, 25 Nov 2016 15:09:22 +0000

Research Seminar in Probability and Statistics I  #2
<p><b>Distributed and
robust network localization</b></p>
<p><b>Cláudia Soares </b>(ISR,
Lisbon)
</p><p><b>October </b>11<b> </b>(Tue.),
<b>11:00</b>  Room <b>P3.10</b> (Math. Building, IST, Av. Rovisco Pais,
1049001 Lisboa)
</p><p>Signal processing over networks has
been a broad and hot topic in the last few years. In most applications networks
of agents typically rely on known node positions, even if the main goal of the
network is not localization. Also, mobile agents need localization for, e.g.,
motion planning, or formation control, where GPS might not be an option. Also,
realworld conditions imply noisy environments, and the network realtime
operation calls for fast and reliable estimation of the agents’ locations. So,
galvanized by the compelling applications researchers have dedicated a great
amount of work to finding the nodes in networks. With the growing network sizes
of devices constrained in energy expenditure and computation power, the need
for simple, fast, and distributed algorithms for network localization spurred
this work. Here, we approach the problem starting from minimal data collection,
aggregating only range measurements and a few landmark positions. We explore
tailored solutions recurring to the optimization and probability tools that can
leverage performance under noisy and unstructured environments. Thus, the
contributions are, mainly:
</p><p>• Distributed localization
algorithms characterized for their simplicity but also strong guarantees;</p>
<p>• Analyses of convergence, iteration
complexity, and optimality bounds for the designed procedures;</p>
<p>• Novel majorization approaches
which are tailored to the specific problem structure.</p>
<p> </p>
<p><a href="http://math.tecnico.ulisboa.pt/seminars/pe/">http://math.tecnico.ulisboa.pt/seminars/pe/</a></p>
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi2
anafh@tecnico.ulisboa.pt (Ana Maria Santos Ferreira Gorjão Henriques)
https://fenix.tecnico.ulisboa.pt/disciplinas/SIPE9/20162017/1semestre/verpost/researchseminarinprobabilityandstatisticsi2#282024733214517
Anúncios
Wed, 05 Oct 2016 13:38:34 +0100