Objective
The availability of many interesting datasets consisting of count time series has motivated a steadily increasing research activity towards the development of appropriate statistical models. Nowadays, a variety of time series models constructed on the basis of the integer-valued property of count data is available. However, their practical usefulness is often limited because of difficulties to implement efficient estimation procedures. These difficulties grow significantly when higher-order autoregressive and moving average terms are included in the model or when multivariate time series data are considered. The SCouT project aims to enhance the flexibility of time series models for counts and facilitate their application to data characterized by complex dependence structures. To this end, the SCouT project proposes an innovative methodological approach that integrates two powerful statistical tools, that is sparsity techniques and composite likelihood methods. The project will provide a unified framework for simultaneous order selection and estimation of autoregressive and moving average terms in count time series models, reducing considerably the computational burden of traditional model selection approaches and improving the predictive performance of the fitted model. The potential of the suggested methodology will be further highlighted by investigating its extensions to spatial and spatio-temporal data that are usually characterized by complex dependence structures. Such data are often met in the field of temporal and spatial analysis of public health surveillance data that will be the main application field of the project. The simultaneous order selection and estimation procedure established by the SCouT project will offer great support to statistical methods for public health surveillance and significantly contribute to the achievement of the effective and timely detection of disease outbreaks.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences software
- medical and health sciences health sciences public health epidemiology epidemics prevention
- social sciences economics and business economics
- medical and health sciences health sciences infectious diseases
- natural sciences mathematics applied mathematics statistics and probability
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2015
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
30123 VENEZIA
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.