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[null,"1.","Record Nr.",null,"UNISA990001167110203316"]
[null,null,"Autore",null,"KERTÉSZ, Imre"]
[null,null,"Titolo",null,"Dossier K. / Imre Kertész ; traduzione di Marinella D'Alessandro"]
[null,null,"Pubbl/distr/stampa",null,"Milano : Feltrinelli, 2009"]
[null,null,"ISBN",null,"978-88-07-01797-1"]
[null,null,"Descrizione fisica",null,"191 p. ; 22 cm"]
[null,null,"Collana",null,"I narratori"]
[null,null,"Disciplina",null,"894.511334"]
[null,null,"Collocazione",null,"VIII.2.A. 246"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Interviste"]
[null,"2.","Record Nr.",null,"UNISALENTO991000845229707536"]
[null,null,"Autore",null,"Ledwith, Margaret"]
[null,null,"Titolo",null,"Participatory practice : community-based action for transformative change / Margaret Ledwith and Jane Springett"]
[null,null,"Pubbl/distr/stampa",null,"Bristol, UK ; Portland, OR : Policy Press, 2010"]
[null,null,"ISBN",null,"9781847420121"]
[null,null,"Descrizione fisica",null,"VII, 252 p. : ill. ; 24 cm"]
[null,null,"Disciplina",null,"360"]
[null,null,"Soggetti",null,"Community development"]
[{"$nulls":4},"Evoluzione sociale"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Include riferimenti bibliografici (p. 223-241) e indice"]
[null,"3.","Record Nr.",null,"UNINA9910438030503321"]
[null,null,"Autore",null,"Kharin Yuriy"]
[null,null,"Titolo",null,"Robustness in Statistical Forecasting / / by Yuriy Kharin"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013"]
[null,null,"ISBN",null,"3-319-00840-4"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (369 p.)"]
[null,null,"Disciplina",null,"330.015195"]
[{"$nulls":4},"519"]
[{"$nulls":4},"519.2"]
[{"$nulls":4},"519.5"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Probabilities"]
[{"$nulls":4},"Engineering mathematics"]
[{"$nulls":4},"Engineering - Data processing"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Probability Theory"]
[{"$nulls":4},"Statistics in Business, Management, Economics, Finance, Insurance"]
[{"$nulls":4},"Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences"]
[{"$nulls":4},"Mathematical and Computational Engineering Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Preface -- Symbols and Abbreviations -- Introduction -- A Decision-Theoretic Approach to Forecasting -- Time Series Models of Statistical Forecasting -- Performance and Robustness Characteristics in Statistical Forecasting -- Forecasting under Regression Models of Time Series -- Robustness of Time Series Forecasting Based on Regression Models -- Optimality and Robustness of ARIMA Forecasting -- Optimality and Robustness of Vector Autoregression Forecasting under Missing Values -- Robustness of Multivariate Time Series Forecasting Based on Systems of Simultaneous Equations -- Forecasting of Discrete Time Series -- Index."]
[null,null,null,"Sommario/riassunto","Traditional procedures in the statistical forecasting of time series, which are proved to be optimal under the hypothetical model, are often not robust under relatively small distortions (misspecification, outliers, "]
[{"$nulls":4},"missing values, etc.), leading to actual forecast risks (mean square errors of prediction) that are much higher than the theoretical values. This monograph fills a gap in the literature on robustness in statistical forecasting, offering solutions to the following topical problems: - developing mathematical models and descriptions of typical distortions in applied forecasting problems; - evaluating the robustness for traditional forecasting procedures under distortions; - obtaining the maximal distortion levels that allow the “safe” use of the traditional forecasting algorithms; - creating new robust forecasting procedures to arrive at risks that are less sensitive to definite distortion types.      ."]