{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"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":49,"n_cols":5,"rows_kept":49,"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],[8,2,8,3],[9,2,9,3],[10,2,10,3],[11,2,11,3],[12,2,12,3],[13,2,13,3],[17,2,17,3],[20,2,20,3],[20,4,20,5],[21,2,21,3],[21,4,21,5],[22,2,22,3],[22,4,22,5],[23,2,23,3],[24,2,24,3],[35,2,35,3],[36,2,36,3],[37,2,37,3],[41,2,41,3],[42,2,42,3],[46,2,46,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910966839303321"]
[null,null,"Titolo",null,"Handbook of capture-recapture analysis / / edited by Steven C. Amstrup, Trent L. McDonald, and Bryan F.J. Manly"]
[null,null,"Pubbl/distr/stampa",null,"Princeton, N.J., : Princeton University Press, c2005"]
[null,null,"ISBN",null,"9786612964831"]
[{"$nulls":4},"9781282964839"]
[{"$nulls":4},"1282964836"]
[{"$nulls":4},"9781400837717"]
[{"$nulls":4},"1400837715"]
[null,null,"Edizione",null,"[Course Book]"]
[null,null,"Descrizione fisica",null,"1 online resource (334 p.)"]
[null,null,"Disciplina",null,"591.7/88/015118"]
[null,null,"Soggetti",null,"Animal populations - Mathematical models"]
[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 (p. [281]-299) and index."]
[null,null,"Nota di contenuto",null,"; Introduction to the handbook / Bryan F.J. Manly ... [et al.] -- Classical closed-population capture-recapture models / Anne Chao, Richard M. Huggins -- Classical open-population capture-recapture models / Kenneth H. Pollock, Russell Alpizar-Jara -- Modern closed-population capture-recapture models / Anne Chao, Richard M. Huggins -- Modern open-population capture-recapture models / James D. Nichols -- Tag-recovery models / John M. Hoenig ... [et al.] -- Joint modeling of tag-recovery and live-resighting data / Richard J. Barker -- Multistate models / Carl J. Schwarz -- Examples / Trent L. McDonald ... [et al.] -- Capture-recapture methods in practice / Bryan F.J. Manly ... [et al.] -- ; Appendix -- ; A.1. Capability matrix for common capture-recapture software packages -- ; A.2. General and contact information for common capture-recapture software packages listed in Table A.1."]
[null,null,null,"Sommario/riassunto","Every day, biologists in parkas, raincoats, and rubber boots go into the field to capture and mark a variety of animal species. Back in the office, statisticians create analytical models for the field biologists' data. But many times, representatives of the two professions do not fully understand one another's roles. This book bridges this gap by helping biologists understand state-of-the-art statistical methods for analyzing capture-recapture data. In so doing, statisticians will also become more familiar with the design of field studies and with the real-life issues facing biologists. Reliable outcomes of capture-"]
[{"$nulls":4},"recapture studies are vital to answering key ecological questions. Is the population increasing or decreasing? Do more or fewer animals have a particular characteristic? In answering these questions, biologists cannot hope to capture and mark entire populations. And frequently, the populations change unpredictably during a study. Thus, increasingly sophisticated models have been employed to convert data into answers to ecological questions. This book, by experts in capture-recapture analysis, introduces the most up-to-date methods for data analysis while explaining the theory behind those methods. Thorough, concise, and portable, it will be immensely useful to biologists, biometricians, and statisticians, students in both fields, and anyone else engaged in the capture-recapture process."]
[null,"2.","Record Nr.",null,"UNINA9911006576403321"]
[null,null,"Autore",null,"Remy Nicolas <1975->"]
[null,null,"Titolo",null,"Applied geostatistics with SGeMS : a user's guide / / Nicolas Remy, Alexandre Boucher and Jianbing Wu"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge : , : Cambridge University Press, , 2009"]
[null,null,"ISBN",null,"1-139-15437-0"]
[{"$nulls":4},"1-107-19010-X"]
[{"$nulls":4},"1-139-23479-X"]
[{"$nulls":4},"1-283-34099-2"]
[{"$nulls":4},"9786613340993"]
[{"$nulls":4},"1-139-15997-6"]
[{"$nulls":4},"1-139-16097-4"]
[{"$nulls":4},"1-139-15541-5"]
[{"$nulls":4},"1-139-15716-7"]
[{"$nulls":4},"1-139-15892-9"]
[{"$nulls":4},"1-139-15001-4"]
[null,null,"Descrizione fisica",null,"1 online resource (xix, 264 pages) : digital, PDF file(s)"]
[null,null,"Disciplina",null,"550.72/7"]
[null,null,"Soggetti",null,"Geological modeling - Computer simulation"]
[{"$nulls":4},"Geological modeling - Statistical methods"]
[{"$nulls":4},"Geology - Computer simulation"]
[{"$nulls":4},"Geology - Statistical methods"]
[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","Title from publisher's bibliographic system (viewed on 05 Oct 2015)."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Introduction -- General overview -- Geostatistics : a recall of concepts -- Data sets and SGeMS EDA tools -- Variogram computation and modeling -- Common parameter input interfaces -- Estimation algorithms -- Stochastic simulation algorithms -- Utilities -- Scripting, commands and plug-ins."]
[null,null,null,"Sommario/riassunto","The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, "]
[{"$nulls":4},"demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering."]