Welcome to Central Library, SUST

Introduction to probability and statistics for ecosystem managers : (Record no. 64160)

MARC details
000 -LEADER
fixed length control field 10370cam a2200817 i 4500
001 - CONTROL NUMBER
control field sulb-eb0032508
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20170713221333.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr |||||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130417s2013 enk ob 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2013015799
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency DLC
Modifying agency YDX
-- N$T
-- E7B
-- DG1
-- CUS
-- YDXCP
-- UBY
-- RRP
-- OCLCQ
-- COO
-- EBLCP
-- DG1
-- BD-SySUS
019 ## -
-- 961637312
-- 962650389
-- 966480619
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118636237
Qualifying information (ePub)
International Standard Book Number 1118636236
Qualifying information (ePub)
International Standard Book Number 9781118636220
Qualifying information (Adobe PDF)
International Standard Book Number 1118636228
Qualifying information (Adobe PDF)
International Standard Book Number 9781118636244
Qualifying information (MobiPocket)
International Standard Book Number 1118636244
Qualifying information (MobiPocket)
International Standard Book Number 1118636201
Qualifying information (electronic bk.)
International Standard Book Number 9781118636206
Qualifying information (electronic bk.)
Canceled/invalid ISBN 9781118357682
Qualifying information (cloth)
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC)
OCLC library identifier AU@
System control number 000050856232
OCLC library identifier CHBIS
System control number 010026960
OCLC library identifier CHVBK
System control number 306231689
OCLC library identifier DKDLA
System control number 820120-katalog:000664378
OCLC library identifier NZ1
System control number 15341737
OCLC library identifier NZ1
System control number 15905502
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)841051232
Canceled/invalid control number (OCoLC)961637312
-- (OCoLC)962650389
-- (OCoLC)966480619
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QH77.3.S73
072 #7 - SUBJECT CATEGORY CODE
Subject category code BUS
Subject category code subdivision 072000
Source bisacsh
Subject category code NAT
Subject category code subdivision 011000
Source bisacsh
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 333.72
Edition number 23
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Haas, Timothy C.
245 10 - TITLE STATEMENT
Title Introduction to probability and statistics for ecosystem managers :
Remainder of title simulation and resampling /
Statement of responsibility, etc. Timothy C. Haas, Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, USA.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Chichester, West Sussex, United Kingdom :
Name of producer, publisher, distributor, manufacturer Wiley,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement Statistics in practice
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Print version record and CIP data provided by publisher.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction -- 1.1. The textbook's purpose -- 1.1.1. The textbook's focus on ecosystem management -- 1.1.2. Reader level, prerequisites, and typical reader jobs -- 1.2. The textbook's pedagogical approach -- 1.2.1. General points -- 1.2.2. Use of this textbook for self-study -- 1.2.3. Learning resources -- 1.3. Chapter summaries -- 1.4. Installing and running R Commander -- 1.4.1. Running R -- 1.4.2. Starting an R Commander session -- 1.4.3. Terminating an R Commander session -- 1.5. Introductory R Commander session -- 1.6. Teaching probability through simulation -- 1.6.1. The frequentist statistical inference paradigm -- 1.7. Summary -- 2. Probability and simulation -- 2.1. Introduction -- 2.2. Basic probability -- 2.2.1. Definitions -- 2.2.2. Independence -- 2.3. Random variables -- 2.3.1. Definitions -- 2.3.2. Simulating random variables -- 2.3.3.A random variable's expected value (mean) and variance -- 2.3.4. Details of the normal (Gaussian) distribution.
Formatted contents note 2.3.5. Distribution approximations -- 2.4. Joint distributions -- 2.4.1. Definition -- 2.4.2. Mixed variables -- 2.4.3. Marginal distribution -- 2.4.4. Conditional distributions -- 2.4.5. Independent random variables -- 2.5. Influence diagrams -- 2.5.1. Definitions -- 2.5.2. Example of a Bayesian network in ecosystem management -- 2.5.3. Modeling causal relationships with an influence diagram -- 2.6. Advantages of influence diagrams in ecosystem management -- 2.7. Two ecosystem management Bayesian networks -- 2.7.1. Waterbody eutrophication -- 2.7.2. Wildlife population viability -- 2.8. Influence diagram sensitivity analysis -- 2.9. Drawbacks to influence diagrams -- 3. Application of probability: Models of political decision making in ecosystem management -- 3.1. Introduction -- 3.2. Influence diagram models of decision making -- 3.2.1. Ecosystem status perception nodes -- 3.2.2. Image nodes -- 3.2.3. Economic, militaristic, and institutional goal nodes.
Formatted contents note 3.2.4. Audience effect nodes -- 3.2.5. Resource nodes -- 3.2.6. Action and target nodes -- 3.2.7. Overall goal attainment node -- 3.2.8. How a group influence diagram reaches a decision -- 3.2.9. An advantage of this decision-making architecture -- 3.2.10. Evaluation dimensions -- 3.3. Rhino poachers: A simplified model -- 3.4. Policymakers: A simplified model -- 3.5. Conclusions -- 4. Statistical inference I: Basic ideas and parameter estimation -- 4.1. Definitions of some fundamental terms -- 4.2. Estimating the PDF and CDF -- 4.2.1. Histograms -- 4.2.2. Ogive -- 4.3. Measures of central tendency and dispersion -- 4.4. Sample quantiles -- 4.4.1. Sample quartiles -- 4.4.2. Sample deciles and percentiles -- 4.5. Distribution of a statistic -- 4.5.1. Basic setup in statistics -- 4.5.2. Sampling distributions -- 4.5.3. Normal quantile-quantile plot -- 4.6. The central limit theorem -- 4.7. Parameter estimation -- 4.7.1. Bias, variance, and efficiency -- 4.8. Interval estimates.
Formatted contents note 5.4.4. Testing for equal variances -- 5.5. Hypothesis tests on the regression model -- 5.5.1. Prediction and estimation confidence intervals -- 5.5.2. Multiple regression -- 5.5.3. Original scale prediction in regression -- 5.6. Brief introduction to vectors and matrices -- 5.6.1. Basic definitions -- 5.6.2. Inverse of a matrix -- 5.6.3. Random vectors and random matrices -- 5.7. Matrix form of multiple regression -- 5.7.1. Generalized least squares -- 5.8. Hypothesis testing with the delete-d jackknife -- 5.8.1. Background -- 5.8.2.A one-sample delete-d jackknife test -- 5.8.3. Testing classifier error rates -- 5.8.4. Important points about this test -- 5.8.5. Parameter confidence intervals -- 6. Introduction to spatial statistics -- 6.1. Overview -- 6.1.1. Types of spatial processes -- 6.2. Spatial statistics and GIS -- 6.2.1. Types of spatial data -- 6.3. QGIS -- 6.3.1. Capabilities -- 6.3.2. Installing QGIS -- 6.3.3. Documentation and tutorials -- 6.3.4. Installing plugins.
Formatted contents note 6.3.5. How to convert a text file to a shapefile -- 6.4. Continuous spatial processes -- 6.4.1. Definitions -- 6.4.2. Graphical tools for exploring continuous spatial data -- 6.4.3. Third- and fourth-order cumulant minimization -- 6.4.4. Best linear unbiased predictor -- 6.4.5. Kriging variance -- 6.4.6. Model-fitting diagnostics -- 6.4.7. Kriging within a window -- 6.5. Spatial point processes -- 6.5.1. Definitions -- 6.5.2. Marked spatial point processes -- 6.5.3. Conclusions -- 6.6. Continuously valued multivariate processes -- 6.6.1. Fitting multivariate covariance functions -- 6.6.2. Cokriging: The MWRCK procedure -- 7. Introduction to spatio-temporal statistics -- 7.1. Introduction -- 7.2. Representing time in a GIS -- 7.2.1. The QGIS Time Manager plugin -- 7.2.2.A Clifford algebra-based spatio-temporal data structure -- 7.2.3.A raster- and event-based spatio-temporal data model -- 7.2.4. Application of ESTDM to a land cover study.
Formatted contents note 7.3. Spatio-temporal prediction: MCSTK -- 7.3.1. Algorithms -- 7.3.2. Covariogram model and its estimator -- 7.4. Multivariate processes -- 7.4.1. Definitions -- 7.4.2. Transformations -- 7.4.3. Covariograms and cross-covariograms -- 7.4.4. Parameter estimation -- 7.4.5. Prediction algorithms -- 7.4.6. Cross-validation -- 7.4.7. Summary -- 7.5. Spatio-temporal point processes -- 7.6. Marked spatio-temporal point processes -- 7.6.1.A mark semivariogram estimator -- 8. Application of statistical inference: Estimating the parameters of an individual-based model -- 8.1. Overview -- 8.2.A simple IBM and its estimation -- 8.2.1. Simple IBM -- 8.2.2. Parameter estimation -- 8.3. Fitting IBMs with MSHD -- 8.3.1. Ergodicity -- 8.3.2. Observable random variables from IBM output -- 8.4. Further properties of parameter estimators -- 8.4.1. Consistency -- 8.4.2. Robustness -- 8.5. Parameter confidence intervals for a nonergodic model -- 8.6. Rhino-supporting ecosystem influence diagram.
Formatted contents note 8.6.1. Spatial effects on poaching -- 8.6.2. IBM variables -- 8.6.3. Initial conditions and hypothesis values of parameters -- 8.6.4. Mapping functions -- 8.6.5. Realism of ecosystem influence diagram output -- 8.7. Estimation of rhino IBM parameters -- 8.7.1. Parameter confidence intervals -- 9. Guiding an influence diagram's learning -- 9.1. Introduction -- 9.2. Online learning of Bayesian network parameters -- 9.2.1. Basic algorithm using simulation -- 9.2.2. Updating influence diagrams -- 9.3. Learning an influence diagram's structure -- 9.3.1. Minimum description length score function -- 9.3.2. Description length of an edge -- 9.3.3. Random generation of DAGs -- 9.3.4. Algorithm to detect and delete cycles -- 9.3.5. Mutate functions -- 9.3.6. MDLEP algorithm -- 9.3.7. Using MDLEP to learn influence diagram structure -- 9.4. Feedback-based learning for group decision-making diagrams -- 9.4.1. Definitions and algorithm -- 9.5. Summary and conclusions.
Formatted contents note 10. Fitting and testing a political-ecological simulator -- 10.1. Introduction -- 10.1.1. Background on rhino poaching -- 10.1.2. Scenarios wherein rhino poaching is reduced -- 10.2. EMT simulator construction -- 10.2.1. Modeled groups -- 10.2.2. Rhino-supporting ecosystem influence diagram -- 10.3. Consistency analysis estimates of simulator parameters -- 10.4. MPEMP computation -- 10.4.1. Setup -- 10.4.2. Solution -- 10.5. Conclusions.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Ecosystem management
General subdivision Statistical methods.
Topical term or geographic name as entry element BUSINESS & ECONOMICS
General subdivision Development
-- Sustainable Development.
Source of heading or term bisacsh
Topical term or geographic name as entry element NATURE
General subdivision Environmental Conservation & Protection.
Source of heading or term bisacsh
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
Genre/form data or focus term Electronic books.
Source of term local
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lubar, Sheldon B.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Main entry heading Haas, Timothy C.
Title Introduction to probability and statistics for ecosystem managers.
Place, publisher, and date of publication Chichester, West Sussex, United Kingdom : John Wiley & Sons Inc., 2013
International Standard Book Number 9781118357682
Record control number (DLC) 2013002861
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Statistics in practice.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://onlinelibrary.wiley.com/book/10.1002/9781118636206">http://onlinelibrary.wiley.com/book/10.1002/9781118636206</a>
Public note Wiley Online Library [Free Download only for SUST IP]
938 ## -
-- EBL - Ebook Library
-- EBLB
-- EBL4037119
-- ebrary
-- EBRY
-- ebr10713658
-- EBSCOhost
-- EBSC
-- 588020
-- YBP Library Services
-- YANK
-- 10745733
-- YBP Library Services
-- YANK
-- 9985179
-- YBP Library Services
-- YANK
-- 12676667
994 ## -
-- 92
-- DG1

No items available.