{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":31,"n_cols":5,"rows_kept":31,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[12,2,12,3],[23,2,23,3],[24,2,24,3],[28,2,28,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910299763803321"]
[null,null,"Titolo",null,"Advances in Complex Data Modeling and Computational Methods in Statistics / / edited by Anna Maria Paganoni, Piercesare Secchi"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015"]
[null,null,"ISBN",null,"3-319-11149-3"]
[null,null,"Edizione",null,"[1st ed. 2015.]"]
[null,null,"Descrizione fisica",null,"1 online resource (210 p.)"]
[null,null,"Collana",null,"Contributions to Statistics, , 2628-8966"]
[null,null,"Disciplina",null,"005.1"]
[{"$nulls":4},"519"]
[{"$nulls":4},"519.5"]
[{"$nulls":4},"570.15195"]
[{"$nulls":4},"620"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Mathematics"]
[{"$nulls":4},"Biometry"]
[{"$nulls":4},"Dynamics"]
[{"$nulls":4},"Nonlinear theories"]
[{"$nulls":4},"Software engineering"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Applications of Mathematics"]
[{"$nulls":4},"Biostatistics"]
[{"$nulls":4},"Applied Dynamical Systems"]
[{"$nulls":4},"Software Engineering"]
[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."]
[null,null,"Nota di contenuto",null,"1 Antonino Abbruzzo, Angelo M. Mineo: Inferring networks from high-dimensional data with mixed variables -- 2 Federico Andreis, Fulvia Mecatti: Rounding Non-integer Weights in Bootstrapping Non-iid Samples: actual problem or harmless practice? -- 3 Marika Arena, Giovanni Azzone, Antonio Conte, Piercesare Secchi, Simone Vantini: Measuring downsize reputational risk in the Oil & Gas industry -- 4 Laura Azzimonti, Marzia A. Cremona, Andrea Ghiglietti, Francesca Ieva, Alessandra Menafoglio, Alessia Pini, Paolo Zanini: BARCAMP Technology Foresight and Statistics for the Future -- 5 Francesca Chiaromonte, Kateryna D. Makova: Using statistics to shed light on the dynamics of "]
[{"$nulls":4},"the human genome: A review -- 6 Nader Ebrahimi, Ehsan S. Soofi and Refik Soyer: Information Theory and Bayesian Reliability Analysis: Recent Advances -- 7 Stephan F. Huckemann: (Semi-) Intrinsic Statistical Analysis on non-Euclidean Spaces -- 8 John T. Kent: An investigation of projective shape space -- 9 Fabio Manfredini, Paola Pucci, Piercesare Secchi, Paolo Tagliolato, Simone Vantini, Valeria Vitelli: Treelet Decomposition of Mobile Phone Data for Deriving City Usage and Mobility Pattern in the Milan Urban Region -- 10 Cristina Mazzali, Mauro Maistriello, Francesca Ieva, Pietro Barbieri: Methodological issues in the use of administrative databases to study heart failure -- 11 Andrea Mercatant: Bayesian inference for randomized experiments with noncompliance and nonignorable missing data -- 12 Antonio Pulcini, Brunero Liseo: Approximate Bayesian Quantile Regression for Panel Data -- 13 Laura M. Sangalli: Estimating surfaces and spatial fields via regression models with differential regularization.  ."]
[null,null,null,"Sommario/riassunto","The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference \"S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction\" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed."]