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Summer School on Modern Statistical Analysis and Computational Methods

Whitaker Institute for Innovation and Societal Change, NUI Galway

Monday, 17 June 2013 at 09:00 - Wednesday, 19 June 2013 at 17:00 (GMT)

Summer School on Modern Statistical Analysis and Comput...

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Type End Quantity
17-18 June: Time Series Analysis Workshop I Ended Free  
19 June: Time Series Analysis Workshop II Ended Free  

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Event Details

HRB’s Clinical Research Facility
Social Sciences Computational Hub at the Whitaker Institute
jointly host the first Summer School on

Statistical Analysis and Computational Methods

June 17-19th, 2013


This year's school will focus on “Time Series Analysis” with applications from a vast array of disciplines ranging from Physiology to Finance. The presentation will be in the form of lecture cum hands-on computer simulation using empirical data from relevant application domains.

The School will run for three days. Professor Dimitris Kugiumtzis from Aristotle University of Thessaloniki, Greece will deliver the first two days, and Mr. Liam Kilmartin from the College of Engineering and Informatics at NUI Galway will conduct the third day’s workshop.  The course outline is below.

Workshop I - June 17th and 18th, 2013
Time Series Analysis: Applications in Physiology, Climate Change and Finance

Presenter: Professor Dimitris Kugiumtzis, Aristotle University of Thessaloniki, Greece.

Duration: This two-day course will run from 9:00am to 5:00pm on Monday 17th & Tuesday 18th June.

Course Content:

Basic characteristics of time series: Stationarity; autocorrelation; removal of trends and seasonality; independence test of time series.

Linear stochastic models for time series: Autoregressive (AR), moving average (MA), autoregressive moving average (ARMA) models for stationary time series; autoregressive integrated moving average (ARIMA) models for non-stationary time series; models for seasonality in the time series; prediction of time series.

Nonlinear analysis of time series: Extensions of linear stochastic models; nonlinear characteristics of time series; nonlinear dynamics and chaos; nonlinear prediction of time series.

Case studies on time series analysis: detecting structural changes in time series records; examples from physiology and finance. Analysis using a stand-alone GUI software.

About Professor Kugiumtzis

Dimitris Kugiumtzis (BSc in Mathematics, MSc and PhD in Informatics) is Associate Professor at the Department of Mathematical, Physical and Computational Sciences, Aristotle University of Thessaloniki, Greece. His main research area is time series analysis in conjunction with dynamical systems and chaos, as well as computational statistics and data mining. Applications extend from physiology to climate and finance. He has published over 40 journal papers and many national and international proceedings papers. He has participated in several national and European research projects, acted as EU evaluator and he is regular reviewer for several journals. He has supervised 4 completed PhD and many MSc.

Workshop II - June 19th, 2013
Time Series Analysis: Signal Processing Methods

Presenter: Liam Kilmartin, NUI Galway

Duration: 9:00 -17:00

Course content:

Basic Time Domain Concepts in Signal Processing: Singal sampling, Fourier decomposition of time domain signals, difference equations, Linear digital filter, filter design, IIR and FIR filters, Periodicity estimation

Frequency Domain Analysis: Fourier analysis, DFT, Impact of DFT window shape and size, Power Spectral Density, Stationarity and frequency domain analysis, revisiting AR(MA) modeling from a frequency domain perspective, introduction to advanced topics such as wavelet analysis, linear coherencesynchrony

Signal Processing Applications: Application of basic signal processing techniques in the fields of physiology, finance and mobile phone based sensing for social science based research; Examples will use Matlab and Android mobile app technology.

About Mr. Kilmartin

Liam Kilmartin received his BE (Electronic Engineering) degree in 1990 and his MEngSc degree in 1994, both from NUI, Galway. He joined the academic staff of the department in 1992 as a temporary teaching appointment and he was appointed to a permanent position in 1994 specialising in the fields of fixed and mobile communication systems. His current research interests focus on the application of signal processing and machine learning techniques in a variety of domains. These include speech, audio and image processing, mobile and fixed network modelling, signal processing and classification algorithms for EEG analysis with specific interest in Brain Computer Interface applications, image processing for biomedical imaging modalities and the application of signal processing to bio-signal analysis in general. He has supervised students to both masters and PhD awards in these areas, funded through IRCSET scholarships and competitive external funding which he has individually attracted, and he has a significant number of publications in international journals and peer reviewed conference proceedings. 


This project is supported by the Irish Social Sciences Platform (ISSP), which is funded under the Programme for Research in Third Level Institutions (Cycle 4), administered by the HEA and co-funded under the European Regional Development Fund (ERDF)


Do you have questions about Summer School on Modern Statistical Analysis and Computational Methods? Contact Whitaker Institute for Innovation and Societal Change, NUI Galway

When & Where

Finnegan Computer Suite, Áras Uí Chathail, NUI Galway

Monday, 17 June 2013 at 09:00 - Wednesday, 19 June 2013 at 17:00 (GMT)

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Whitaker Institute for Innovation and Societal Change, NUI Galway

The Whitaker Institute for Innovation and Societal Change applies a multi-perspective research approach to business and social issues, with an impact-led focus at the core of its endeavours. One of its key values is the promotion of a sustainable and inclusive society, influenced by the broad dissemination of rigorous and relevant research. Furthermore, the Whitaker Institute seeks to continue the tradition at NUI Galway of critically pursuing knowledge discovery that stimulates academic debates and opens public conversation to advance the greater good.

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