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Advances in Neural Data Science : Data Research Camp 2022, Venice, Italy, July 12–15 / / edited by Antonio Canale, Alessandra Luati, Stefano Mazzuco, Raffaella Piccarreta, Nicola Sartori, Piercesare Secchi
Advances in Neural Data Science : Data Research Camp 2022, Venice, Italy, July 12–15 / / edited by Antonio Canale, Alessandra Luati, Stefano Mazzuco, Raffaella Piccarreta, Nicola Sartori, Piercesare Secchi
Autore Canale Antonio
Edizione [1st ed. 2025.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
Descrizione fisica 1 online resource (190 pages)
Disciplina 006.31
Altri autori (Persone) LuatiAlessandra
MazzucoStefano
PiccarretaRaffaella
SartoriNicola
SecchiPiercesare
Collana Springer Proceedings in Mathematics & Statistics
Soggetto topico Machine learning
Machine Learning
Aprenentatge automàtic
Soggetto genere / forma Llibres electrònics
ISBN 9783031706387
3031706382
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto D'Angelo, Exploring the challenges of the analysis of the Allen Brain Observatory dataset -- Alfonzetti, Model free estimation of causal effects of different stimuli on neuron activities -- Barile, Assessing neuron response to external stimuli with a data-driven procedure for spike train extraction and GAMLSS regressions -- Bianco, Bayesian signal extraction in noisy uorescence traces -- Mascaretti and Friel, Bayesian Global-Local Deconvolution of Neurological Data -- Burzacchi, A point process approach for the classification of noisy calcium imaging data -- Girardi, Time Series Methodology for Analyzing Calcium ImagingData.
Record Nr. UNINA-9910983323703321
Canale Antonio  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Developments in demographic forecasting / / edited by Stefano Mazzuco, Nico Keilman
Developments in demographic forecasting / / edited by Stefano Mazzuco, Nico Keilman
Autore Mazzuco Stefano
Edizione [First edition, 2020.]
Pubbl/distr/stampa Springer Nature, 2020
Descrizione fisica 1 online resource (viii, 258 pages) : illustrations; digital, PDF file(s)
Disciplina 304.6
Collana The Springer Series on Demographic Methods and Population Analysis
Soggetto topico Demography
Statistics 
Statistics for Social Sciences, Humanities, Law
Soggetto non controllato Demography
Statistics for Social Sciences, Humanities, Law
Population and Demography
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
Population forecasting
Fertility
Mortality
Migration
Forecasting evaluation
Social Media data
Population statistics
Population modelling
Bayesian population models
Open access
Population & demography
Social research & statistics
ISBN 3-030-42472-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1. Introduction­ -- Chapter 2. Stochastic population forecasting: A Bayesian approach based on evaluation by experts -- Chapter 3. Using expert elicitation to build long-term projection assumptions -- Chapter 4. Post-Transitional Demography and Convergence: What can we Learn from Half a Century of World Population Prospects? -- Chapter 5. Projecting Proportionate Age–Specific Fertility Rates via Bayesian Skewed Processes -- Chapter 6. A Three-component Approach to Model and Forecast Age-at-death Distributions -- Chapter 7. Alternative forecasts of Danish life expectancy -- Chapter 8. Coherent mortality forecasting with standards: low mortality serves as a guide -- Chapter 9. European mortality forecasts: Are the targets still moving? -- Chapter 10. Bayesian disaggregated forecasts: Internal migration in Iceland -- Chapter 11. Forecasting origin-destination-age-sex migration flow tables with multiplicative components -- Chapter 12. New Approaches to the Conceptualization and Measurement of Age and Ageing.
Record Nr. UNINA-9910418324703321
Mazzuco Stefano  
Springer Nature, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui