Locally Stationary Time Series and Multiscale Methods for Statistics (LuSTruM)
Lead Research Organisation:
University of Bristol
Department Name: Mathematics
Abstract
This fellowship proposes research in time series analysis and regression. Time series
analysis is concerned with data recorded through time. Time series occur in a variety
of areas of great importance to society such as medicine (recording of vital signs),
economics and finance (GDP or share prices), the environment (air pollution),
energy (national electricity demand), and transportation (traffic flow), to name but a few.
A common way of displaying time series, often seen in the media, is via the time plot,
which plots the series' values consecutively through time enabling major features,
such as trend or seasonal effects, to be readily observed. Collectively, society needs
to ensure that series are properly collected and recorded, modelled appropriately,
to gain an understanding of their behaviour, and often predicted to estimate their
future values (forecasting).
Much real world analysis assumes that series arise from stationary models, which
permit the values of the series to change at each time, but the underlying statistics
do not change (for example, a stationary share price changes from hour to hour,
but the overall level, or mean, stays constant). It is becoming increasingly clear that
stationary models are not appropriate for many real series. For example, share price
statistics do change, sometimes exceptionally, due to sudden events such as political
upheaval or natural disasters, and often nonstationary models are appropriate and
useful alternatives.
This project intends to develop nonstationary techniques with a focus on energy and
economics applications. For example, energy companies are interested in nonstationary
models because deregulation and increasingly diverse energy sources have caused
many previously stable data sets to become less stationary and more unpredictable.
This project will create new nonstationary models intended to be more realistic, flexible and
lead to better modelling, forecasting and consequently better decision-making.
Nonstationary models can also shed light on tasks that are infeasible for stationary ones
such as ascertaining whether a series has been sampled frequently enough. We will also
research nonstationary functional models, where each observation is not a single number
but an entire curve, such as national electricity consumption recorded across a day.
Regression is concerned with the modelling of relationships between different variables
and is used extensively in the real world. Many important regression methods assume
that data have constant variance and a `bell-curve' distribution. Much real data are not
like that, but operations, such as taking each observation's square root, can make the
data fulfil those constant variance/`bell curve' assumptions, at least approximately.
Recently, a new, promising, very different, multiscale class, called the Haar-Fisz transform,
was developed. The new class works extremely well for count data and has shown some
fascinating theoretical properties, such as mimicking the well-known logarithm. This project
will investigate the intriguing theoretical underpinnings of this new class as well as develop
further methods for cleaning up noisy signals, for example, removing noise from astronomical
or low-light security images. Additionally, we will investigate regression for irregular data
using techniques that make use of multiple scales simultaneously (multiscale).
First generation multiscale methods, highly valued for purposes such as image compression
in JPEG, are not easily adapted to irregular situations. This project seeks to investigate
second generation multiscale methods, suitable for irregular data. For example, to better
estimate and control information on networks (such as identify and mitigate delays on
transport networks) or irregularly-spaced systems (such as identify regions of the genome
that are implicated in several complex diseases such as cancer.)
analysis is concerned with data recorded through time. Time series occur in a variety
of areas of great importance to society such as medicine (recording of vital signs),
economics and finance (GDP or share prices), the environment (air pollution),
energy (national electricity demand), and transportation (traffic flow), to name but a few.
A common way of displaying time series, often seen in the media, is via the time plot,
which plots the series' values consecutively through time enabling major features,
such as trend or seasonal effects, to be readily observed. Collectively, society needs
to ensure that series are properly collected and recorded, modelled appropriately,
to gain an understanding of their behaviour, and often predicted to estimate their
future values (forecasting).
Much real world analysis assumes that series arise from stationary models, which
permit the values of the series to change at each time, but the underlying statistics
do not change (for example, a stationary share price changes from hour to hour,
but the overall level, or mean, stays constant). It is becoming increasingly clear that
stationary models are not appropriate for many real series. For example, share price
statistics do change, sometimes exceptionally, due to sudden events such as political
upheaval or natural disasters, and often nonstationary models are appropriate and
useful alternatives.
This project intends to develop nonstationary techniques with a focus on energy and
economics applications. For example, energy companies are interested in nonstationary
models because deregulation and increasingly diverse energy sources have caused
many previously stable data sets to become less stationary and more unpredictable.
This project will create new nonstationary models intended to be more realistic, flexible and
lead to better modelling, forecasting and consequently better decision-making.
Nonstationary models can also shed light on tasks that are infeasible for stationary ones
such as ascertaining whether a series has been sampled frequently enough. We will also
research nonstationary functional models, where each observation is not a single number
but an entire curve, such as national electricity consumption recorded across a day.
Regression is concerned with the modelling of relationships between different variables
and is used extensively in the real world. Many important regression methods assume
that data have constant variance and a `bell-curve' distribution. Much real data are not
like that, but operations, such as taking each observation's square root, can make the
data fulfil those constant variance/`bell curve' assumptions, at least approximately.
Recently, a new, promising, very different, multiscale class, called the Haar-Fisz transform,
was developed. The new class works extremely well for count data and has shown some
fascinating theoretical properties, such as mimicking the well-known logarithm. This project
will investigate the intriguing theoretical underpinnings of this new class as well as develop
further methods for cleaning up noisy signals, for example, removing noise from astronomical
or low-light security images. Additionally, we will investigate regression for irregular data
using techniques that make use of multiple scales simultaneously (multiscale).
First generation multiscale methods, highly valued for purposes such as image compression
in JPEG, are not easily adapted to irregular situations. This project seeks to investigate
second generation multiscale methods, suitable for irregular data. For example, to better
estimate and control information on networks (such as identify and mitigate delays on
transport networks) or irregularly-spaced systems (such as identify regions of the genome
that are implicated in several complex diseases such as cancer.)
Planned Impact
The beneficiaries of the proposed research fall into two groups: direct and indirect.
The direct beneficiaries consist of Shell Research, the Bank of England and Prof. Ina Hoeschele and the wider medical team at the Virginia Bioinformatics Institute (VBI) and the Wake Forest School of Medicine: these groups are named and their interests are explained in the proposal and pathways to impact document. I intend to work closely with these beneficiaries and provide added value as described in the proposal in each case. For example, the VBI would value being able to use the "best-in-class" signal extraction benefits of wavelets (which they already use) but directly on irregularly spaced data via lifting (which we will work on); the Bank of England is interested in new approaches to financial stability and, in particular, the benefits of local stationarity for economic modelling in terms of more accurate forecasts or attempting to understand the sampling scheme that gives maximum information to such public bodies with least cost; Shell, like many other energy companies, are interested in many aspects of nonstationarity particularly the multivariate situation in a world where massively high-dimensional data collection is a reality. Specific aspects of the project, of interest to particular partners, is described in the Case for Support.
Another important group of indirect beneficiaries are the energy companies that I am already working with on a separate EPSRC grant (LETS) funded by the Mathematics and Energy programme. These energy companies are EDF (Paris), Vattenfall and GL Garrad Hassan. The current proposal and the Maths/Energy proposal are supportive and complementary in the sense that the latter has a narrower focus on energy-related issues, and also a small amount of my time. However, it is likely that new developments in the current proposal will also be of interest to these energy partners (for example, continuous time nonstationary processes, new regression methods) and we would seek to continue any productive LETS interactions as part of this proposal after LETS finishes in March 2015. On the (statistical) economics side we are building relationships with Antonis Michis at the Central Bank of Cyprus who has already worked on applications of multiscale methods to economics.
Another key group of beneficiaries will be the RAs themselves and, in particular, those organisations that later employ them or work with them. I have a strong record of developing excellent people and helping them start productive academic and non-academic careers. Many of these people are themselves further creating and innovating in cognate statistical areas and this is a powerful way of initiating impact.
Another constituency are those that will take ideas and, particularly, software developed by the proposed research. Much of what we develop is generic and can be used in many application areas where time series or regression problems occur. It is difficult to quantify precisely the number and identity of such groups who might use our work. However, from our experience with earlier software, such as WaveThresh, it is clear that the distribution and use of such free software is very wide, both in terms of research publications that use such software and in direct communication with users in banking (Bank of America, Reserve Bank of New Zealand), government (Centers for Disease Control, NIMR-MRC, NIST, Los Alamos National Lab) and industry (Detica, Merck, AC Nielsen, Plant Automation Services, Siemens, Unilever) and a large number in academic institutions.
Overall, we intend our impact to be specific (with the partners mentioned) and generic/widespread as a result of our publications and software. Through these routes we intend to have a positive impact on national/global economic competitiveness, increasing the efficiency of analysis, forecasting and hence policy and enhancing health through our bioinformatics work.
The direct beneficiaries consist of Shell Research, the Bank of England and Prof. Ina Hoeschele and the wider medical team at the Virginia Bioinformatics Institute (VBI) and the Wake Forest School of Medicine: these groups are named and their interests are explained in the proposal and pathways to impact document. I intend to work closely with these beneficiaries and provide added value as described in the proposal in each case. For example, the VBI would value being able to use the "best-in-class" signal extraction benefits of wavelets (which they already use) but directly on irregularly spaced data via lifting (which we will work on); the Bank of England is interested in new approaches to financial stability and, in particular, the benefits of local stationarity for economic modelling in terms of more accurate forecasts or attempting to understand the sampling scheme that gives maximum information to such public bodies with least cost; Shell, like many other energy companies, are interested in many aspects of nonstationarity particularly the multivariate situation in a world where massively high-dimensional data collection is a reality. Specific aspects of the project, of interest to particular partners, is described in the Case for Support.
Another important group of indirect beneficiaries are the energy companies that I am already working with on a separate EPSRC grant (LETS) funded by the Mathematics and Energy programme. These energy companies are EDF (Paris), Vattenfall and GL Garrad Hassan. The current proposal and the Maths/Energy proposal are supportive and complementary in the sense that the latter has a narrower focus on energy-related issues, and also a small amount of my time. However, it is likely that new developments in the current proposal will also be of interest to these energy partners (for example, continuous time nonstationary processes, new regression methods) and we would seek to continue any productive LETS interactions as part of this proposal after LETS finishes in March 2015. On the (statistical) economics side we are building relationships with Antonis Michis at the Central Bank of Cyprus who has already worked on applications of multiscale methods to economics.
Another key group of beneficiaries will be the RAs themselves and, in particular, those organisations that later employ them or work with them. I have a strong record of developing excellent people and helping them start productive academic and non-academic careers. Many of these people are themselves further creating and innovating in cognate statistical areas and this is a powerful way of initiating impact.
Another constituency are those that will take ideas and, particularly, software developed by the proposed research. Much of what we develop is generic and can be used in many application areas where time series or regression problems occur. It is difficult to quantify precisely the number and identity of such groups who might use our work. However, from our experience with earlier software, such as WaveThresh, it is clear that the distribution and use of such free software is very wide, both in terms of research publications that use such software and in direct communication with users in banking (Bank of America, Reserve Bank of New Zealand), government (Centers for Disease Control, NIMR-MRC, NIST, Los Alamos National Lab) and industry (Detica, Merck, AC Nielsen, Plant Automation Services, Siemens, Unilever) and a large number in academic institutions.
Overall, we intend our impact to be specific (with the partners mentioned) and generic/widespread as a result of our publications and software. Through these routes we intend to have a positive impact on national/global economic competitiveness, increasing the efficiency of analysis, forecasting and hence policy and enhancing health through our bioinformatics work.
Publications
Cardinali A
(2018)
Practical powerful wavelet packet tests for second-order stationarity
in Applied and Computational Harmonic Analysis
Cardinali A
(2017)
Locally Stationary Wavelet Packet Processes: Basis Selection and Model Fitting
in Journal of Time Series Analysis
Cardinali A
(2013)
Costationarity of Locally Stationary Time Series Using costat
in Journal of Statistical Software
Crossman DJ
(2015)
T-tubule disease: Relationship between t-tubule organization and regional contractile performance in human dilated cardiomyopathy.
in Journal of molecular and cellular cardiology
Das S
(2016)
Measuring the degree of non-stationarity of a time series
in Stat
Eckley I
(2018)
A test for the absence of aliasing or local white noise in locally stationary wavelet time series
in Biometrika
Eckley I
(2014)
Spectral correction for locally stationary Shannon wavelet processes
in Electronic Journal of Statistics
Killick R
(2020)
The local partial autocorrelation function and some applications
in Electronic Journal of Statistics
Knight MI
(2017)
A wavelet lifting approach to long-memory estimation.
in Statistics and computing
Michis A
(2016)
Case study: shipping trend estimation and prediction via multiscale variance stabilisation
in Journal of Applied Statistics
Nason G
(2014)
White noise testing using wavelets
in Stat
Nason G
(2018)
Editorial: Statistical Flaws in the Teaching Excellence and Student Outcomes Framework in UK Higher Education
in Journal of the Royal Statistical Society Series A: Statistics in Society
Nason G
(2017)
Should we Sample a time Series more Frequently?: Decision Support via Multirate Spectrum Estimation
in Journal of the Royal Statistical Society Series A: Statistics in Society
Nason G
(2015)
Bayesian Wavelet Shrinkage of the Haar-Fisz Transformed Wavelet Periodogram.
in PloS one
Nason G
(2014)
Multiscale variance stabilization via maximum likelihood
in Biometrika
Nason G
(2013)
A Test for Second-Order Stationarity and Approximate Confidence Intervals for Localized Autocovariances for Locally Stationary Time Series
in Journal of the Royal Statistical Society Series B: Statistical Methodology
Powell B
(2017)
Optimal Sampling Frequency of Serum Cortisol Concentrations After Cardiac Surgery.
in Critical care medicine
Powell B
(2018)
Tracking and Modelling Prices Using Web-Scraped Price Microdata: Towards Automated Daily Consumer Price Index Forecasting
in Journal of the Royal Statistical Society Series A: Statistics in Society
Remenyi N
(2014)
Image denoising with 2D scale-mixing complex wavelet transforms.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Description | New methods for the analysis of locally stationary time series. This includes new methods for tests of stationarity, new methods for forecasting, new methods for assessing sampling rate, checking aliasing, analysis of network time series. Various software packages produced and uploaded. |
Exploitation Route | Most of our methods are statistical methodologies which can be used by a wide variety of users of time series. |
Sectors | Aerospace Defence and Marine Agriculture Food and Drink Chemicals Communities and Social Services/Policy Construction Creative Economy Digital/Communication/Information Technologies (including Software) Education Electronics Energy Environment Financial Services and Management Consultancy Healthcare Leisure Activities including Sports Recreation and Tourism Government Democracy and Justice Manufacturing including Industrial Biotechology Culture Heritage Museums and Collections Pharmaceu |
URL | http://www.maths.bris.ac.uk/~guy/ |
Description | It is difficult to know about NON-ACADEMIC IMPACT. Most information we get is from applied academic articles. I can cite several papers that cite our work and also make use of various software packages are frequently being used in applied areas. It is extremely difficult to obtain info on non-academic organisations that use our work. There is no recognised database that tracks this and, indeed, corporations tend to keep this information to themselves. Remember, that due to open access rules our work is freely available and journals these days demand software to (sometimes as a condition of publication). So companies can use our work free or charge and we often do not know about it. In terms of academic input our work has been used in academic work on MRI imaging, biomechanics, energy markets, economics, neuroscience, sports science, water quality, circadian rhythms, sleep medicine, turbulence, EEG analysis, shipping, cardiovascular science, social networks and several other areas. |
First Year Of Impact | 2013 |
Sector | Communities and Social Services/Policy,Digital/Communication/Information Technologies (including Software),Energy,Environment,Healthcare,Leisure Activities, including Sports, Recreation and Tourism,Other |
Impact Types | Cultural Societal Economic |
Title | Case study: shipping trend estimation and prediction via multiscale variance stabilisation |
Description | Shipping and shipping services are a key industry of great importance to the economy of Cyprus and the wider European Union. Assessment, management and future steering of the industry, and its associated economy, is carried out by a range of organisations and is of direct interest to a number of stakeholders. This article presents an analysis of shipping credit flow data: an important and archetypal series whose analysis is hampered by rapid changes of variance. Our analysis uses the recently developed data-driven Haar-Fisz transformation that enables accurate trend estimation and successful prediction in these kinds of situation. Our trend estimation is augmented by bootstrap confidence bands, new in this context. The good performance of the data-driven Haar-Fisz transform contrasts with the poor performance exhibited by popular and established variance stabilisation alternatives: the Box-Cox, logarithm and square root transformations. |
Type Of Material | Database/Collection of data |
Year Produced | 2016 |
Provided To Others? | Yes |
URL | https://tandf.figshare.com/articles/dataset/Case_study_shipping_trend_estimation_and_prediction_via_... |
Title | Case study: shipping trend estimation and prediction via multiscale variance stabilisation |
Description | Shipping and shipping services are a key industry of great importance to the economy of Cyprus and the wider European Union. Assessment, management and future steering of the industry, and its associated economy, is carried out by a range of organisations and is of direct interest to a number of stakeholders. This article presents an analysis of shipping credit flow data: an important and archetypal series whose analysis is hampered by rapid changes of variance. Our analysis uses the recently developed data-driven Haar-Fisz transformation that enables accurate trend estimation and successful prediction in these kinds of situation. Our trend estimation is augmented by bootstrap confidence bands, new in this context. The good performance of the data-driven Haar-Fisz transform contrasts with the poor performance exhibited by popular and established variance stabilisation alternatives: the Box-Cox, logarithm and square root transformations. |
Type Of Material | Database/Collection of data |
Year Produced | 2016 |
Provided To Others? | Yes |
URL | https://tandf.figshare.com/articles/dataset/Case_study_shipping_trend_estimation_and_prediction_via_... |
Description | Office for National Statistics |
Organisation | Office for National Statistics |
Country | United Kingdom |
Sector | Private |
PI Contribution | Developed/developing new methods for finding optimal sampling rate for official statistics and also methods for analysing web-scraped price data. |
Collaborator Contribution | Helped with the research, provided data/examples |
Impact | GPN, Powell, B., Elliott, D. and Smith, P. (2017) Should We Sample a Time Series More Frequently? Decision Support via Multirate Spectrum Estimation (With Discussion). J. Roy. Statist. Soc. A, 180, 353--407. Powell, B., Nason, G.P., Elliott, D. Mayhew, M., Davies, J. and Winton, J. (2018) Tracking and modelling prices using web-scraped price microdata: toward automated daily CPI forecasting. J. Roy. Statist. Soc., A. 181, 737--756. |
Start Year | 2013 |
Title | BootWPTOS |
Description | Test Stationarity using Bootstrap Wavelet Packet Tests |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | N/A |
URL | https://cran.r-project.org/web/packages/BootWPTOS/index.html |
Title | Software - GNAR |
Description | Software to model and fit generalized network autoregressive processes. Joint with Kathryn Leeming, Matt Nunes and Marina Knight |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | None yet. |
URL | https://cran.r-project.org/web/packages/GNAR/index.html |
Title | Software - PP3 |
Description | Software to compute three-dimensional projection pursuit solutions of a multivariate data set. This was joint work with Robin Sibson. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | None known at this point |
URL | https://cran.r-project.org/web/packages/PP3/index.html |
Title | Yamm: Multivariate Methods Based on Projections and Related Concepts |
Description | Functionality to compute the projection median via several algorithms. This package also provides functions to plot different multivariate medians and multivariate quantiles in two-dimensional and three-dimensional data respectively. See Chen, F. and Nason, G.P. (2020) "A new method for computing the projection median, its influence curve and techniques for the production of projected quantile plots." PLOS One (accepted for publication). |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
Impact | It's being downloaded at roughly 100 downloads per month |
URL | https://cran.r-project.org/package=Yamm |
Title | hwwntest |
Description | Freeware R software to carry out tests of global white noise |
Type Of Technology | Software |
Year Produced | 2015 |
Open Source License? | Yes |
Impact | Software |
URL | https://cran.r-project.org/web/packages/hwwntest/index.html |
Title | liftLRD |
Description | Wavelet Lifting Estimators of the Hurst Exponent for Regularly and Irregularly Sampled Time Series |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | N/A |
URL | https://cran.r-project.org/web/packages/liftLRD/index.html |
Title | locits |
Description | New test of second-order stationarity and confidence intervals for localized autocovariance |
Type Of Technology | Software |
Year Produced | 2013 |
Open Source License? | Yes |
Impact | Several users in economics and other areas |
URL | http://cran.r-project.org/web/packages/locits/index.html |
Title | regspec |
Description | Non-Parametric Bayesian Spectrum Estimation for Multirate Data |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | Freeware package uploaded to CRAN |
URL | https://cran.r-project.org/web/packages/regspec/index.html |
Description | Birkbeck Seminar |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | An overview of non-stationary spatio-temporal modelling of natural events. Department of Economics, Mathematics and Statistics, Birkbeck given by SD |
Year(s) Of Engagement Activity | 2016 |
Description | CMStatistics Conference: Non-stationary and high-dimensionality in time series analysis |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | International research conference |
Year(s) Of Engagement Activity | 2017 |
Description | Invited Talk Royal Statistical Society International Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Invited Talk, Royal Statistical Society International Conference, Newcastle. |
Year(s) Of Engagement Activity | 2013 |
Description | Invited Talk at COMPSTAT International Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Bayesian nonparametric spectral density estimation: with application to under-sampled time series, Invited Talk at COMPSTAT 2014 conference, Geneva, Switzerland |
Year(s) Of Engagement Activity | 2014 |
Description | Invited Talk at Joint Statistical Meetings 2017 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Optimising Inflation Forecasts based on Web-Scraped price data, Topic Contributed Talk, JSM, Baltimore, 2017 |
Year(s) Of Engagement Activity | 2017 |
Description | Invited Talk, CMStatistics 2015 International Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | CMStatistics 2015, 8th International Conference of the ERCIM Working Group on Computational and Methodological Statistics on 'Robust and Efficient Regression', Senate House, University of London, by GPN |
Year(s) Of Engagement Activity | 2015 |
Description | Invited Talk, Howell Tong 70th Birthday celebration |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Analysis and forecasting of locally stationary time series, Invited Talk, London School of Economics |
Year(s) Of Engagement Activity | 2014 |
URL | http://www.lse.ac.uk/statistics/events/SpecialEventsandConferences/Nonlinear-time-series-analysis/Ho... |
Description | Invited Talk, Office for National Statistics, Time Series Workshop, RSS HQ, London |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Time Series Workshop, talks + interaction activities |
Year(s) Of Engagement Activity | 2015 |
Description | Invited Talk, STOR-i workshop, Lancaster |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Workshop on Analysis of nonstationary multivariate time series, STOR-i Workshop, Lancaster University, UK. |
Year(s) Of Engagement Activity | 2016 |
Description | Invited Talk, Shanghai Centre for Mathematical Sciences |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | 'Some Experiments in Network Time Series', Workshop on Statistical Network and High-Dimensional Data Analysis: Theory and Application, Shanghai Centre for Mathematical Sciences, Shanghai, China. |
Year(s) Of Engagement Activity | 2016 |
Description | Invited Talk: Centre International de Recontres Mathematiques, Luminy, France |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Invited Talk by GPN |
Year(s) Of Engagement Activity | 2016 |
URL | http://library.cirm-math.fr/ListRecord.htm?list=request&table=3&idinlist=0&NumReq=112&cluster_1=naso... |
Description | Invited Talk: Maurice Priestley Commemoration Day |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Talk on wavelet packet processes, Maurice Priestley Commemoration Event, Manchester University |
Year(s) Of Engagement Activity | 2013 |
URL | http://www.maths.manchester.ac.uk/~gb/events/Priestley/MauricePriestley.html |
Description | Invited talk at Royal Statistical Society International Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Should we sample more frequently? Quantifying the cost of under- or over-sampling via a stationary process's spectral density: Invited talk at Royal Statistical Society International Conference 2015, Exeter by BP |
Year(s) Of Engagement Activity | 2015 |
Description | Invited talk at Time Series in official Statistics workshop, London |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Time Series in Official Statistics Workshop, London, organised by the ONS. |
Year(s) Of Engagement Activity | 2017 |
Description | Keynote Talk, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Keynote Talk |
Year(s) Of Engagement Activity | 2014 |
URL | http://newton.cam.ac.uk/seminar/20140113153016301 |
Description | Network Time Series talk to Royal Statistical Society Northern Ireland Local Group |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Network Time Series' Royal Statistical Society Northern Ireland Local Group. |
Year(s) Of Engagement Activity | 2021 |
URL | https://rss.org.uk/news-publication/news-publications/2021/section-group-reports/network-time-series... |
Description | Network Time Series, Alan Turing Institute Scoping Workshop |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Scoping Workshop |
Year(s) Of Engagement Activity | 2015 |
Description | Plenary Lecture, Royal Statistical Society Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Plenary Lecture at Royal Statistical Society Conference, 2016 on "Should we sample a time series more frequently?, by GPN and BP |
Year(s) Of Engagement Activity | 2016 |
Description | Presentation at Joint Statistical Meetings, Denver |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Talk at Joint Statistical Meetings |
Year(s) Of Engagement Activity | 2019 |
Description | Presentation, Joint Statistical Meetings, Chicago, 2016. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Contributed presentation JSM 2016 on "Can we rank a time series for non-stationarity? " by SD |
Year(s) Of Engagement Activity | 2016 |
Description | Research Presentation at European Meeting of Statisticians, Helsinki |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | European Meeting of Statisticians Invited Talk, many interesting discussions + future work discussed |
Year(s) Of Engagement Activity | 2017 |
Description | Research Presentation given to US Census Bureau by BP |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Improving Inflation Forecasts Based on Web-Scraped Price Data to the Center for Statistical Research and Methodology Seminar, US Census Bureau, Washington |
Year(s) Of Engagement Activity | 2017 |
Description | Research Seminar Talk at Southampton University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Policymakers/politicians |
Results and Impact | Research seminar on `A test for aliasing' |
Year(s) Of Engagement Activity | 2018 |
Description | Research Talk at the Alan Turing Institute |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Research talk at the Alan Turing Institute on Network Time Series |
Year(s) Of Engagement Activity | 2018 |
Description | Research presentation at MRC Biostatistics Unit, Cambridge |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Talk to MRC Biostatistics unit, a mixed audience of statisticians and medical associates. |
Year(s) Of Engagement Activity | 2017 |
Description | Royal Statistical Society, South west local group |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Talk to Royal Statistical Society local group - audience was mixed academics/business |
Year(s) Of Engagement Activity | 2019 |
Description | Seminar Glasgow |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Estimation of spatio-temporal parameters in spectral Domain. School of Mathematics and Statistics, University of Glasgow by SD |
Year(s) Of Engagement Activity | 2016 |
Description | Seminar Lancaster Uni |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Estimation of spatio-temporal parameters in spectral Domain. School of Mathematics, Lancaster University by SD |
Year(s) Of Engagement Activity | 2015 |
Description | Seminar at UC Louvain |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Seminar at UC Louvain Belgium on Network Time Series |
Year(s) Of Engagement Activity | 2020 |
Description | Seminar talk, Edinburgh |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Model-based inflation estimation with application to web-scraped data, seminar talk at University of Edinburgh by BP |
Year(s) Of Engagement Activity | 2016 |
Description | Seminar, School of Mathematics and Statistics, University of Melbourne |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Seminar delivered by Sourav Das on Modelling Spatio-Temporal Data |
Year(s) Of Engagement Activity | 2017 |
Description | Talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited talk to ISI World Statistics Congress session on Network Time Series |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.isi2021.org |
Description | Talk at CFE/CM meeting on Computational and Methodological Statistics |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation at International Conference |
Year(s) Of Engagement Activity | 2019 |
Description | Talk at Office for National Statistics, Newport |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation on latest research to ONS professionals |
Year(s) Of Engagement Activity | 2019 |
Description | Talk at TSIMF Workshop on "Complex Time Series Modelling and Forecasting", Sanya China |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | International Research Workshop |
Year(s) Of Engagement Activity | 2018 |
Description | Talk, Royal Statistical Society International Conference, Manchester, 2016 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Talk "Can we rank a time series for non-stationarity? " by SD |
Year(s) Of Engagement Activity | 2016 |
Description | Talk, University of Southampton |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Model-based inflation estimation with application to web-scraped data, seminar talk at Uni. Southampton |
Year(s) Of Engagement Activity | 2016 |
Description | Time Series in Official Statistics Workshop, Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Modelling high-frequency on-line price data, presentation by BP and workshop meetings/discussions |
Year(s) Of Engagement Activity | 2017 |
Description | UCL Big Data Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Research presentation on network time series to UCL Big Data Conference |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.ucl.ac.uk/bigdata-theory/ |
Description | University of Lancaster Seminar Series |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Have I been sampling this time series frequently enough?, University of Lancaster, Statistics: Nonstationary Time Series and Changepoint Seminar Series by BP |
Year(s) Of Engagement Activity | 2015 |
Description | `Calculating the CPI from web-scraped data', Talk, University of York |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Policymakers/politicians |
Results and Impact | `Calculating the CPI from web-scraped data' by BP |
Year(s) Of Engagement Activity | 2017 |