Sampling strategies for natural resources and the environment:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Boca Raton, Fla. [u.a.]
Chapman & Hall/CRC
2008
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013307706&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XX, 474 S. graph. Darst. |
| ISBN: | 9781584883708 1584883707 |
Internformat
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| 100 | 1 | |a Gregoire, Timothy G. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Sampling strategies for natural resources and the environment |c Timothy G. Gregoire ; Harry T. Valentine |
| 246 | 1 | 3 | |a Sampling techniques for natural and environmental resources |
| 264 | 1 | |a Boca Raton, Fla. [u.a.] |b Chapman & Hall/CRC |c 2008 | |
| 300 | |a XX, 474 S. |b graph. Darst. | ||
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| 650 | 4 | |a Sciences de l'environnement - Méthodes statistiques | |
| 650 | 4 | |a Échantillonnage (Écologie) | |
| 650 | 4 | |a Environmental sampling | |
| 650 | 4 | |a Environmental sciences |x Statistical methods | |
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Datensatz im Suchindex
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|---|---|
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| DE-BY-TUM_location | 10 |
| DE-BY-TUM_media_number | 040050712048 |
| _version_ | 1821932362582196224 |
| adam_text | Contents
Preface xvii
1 Introduction 1
1.1 The need for sampling strategies 1
1.2 A medley of sampling scenarios 3
1.2.1 Sampling for biomass estimation 3
1.2.2 Sampling to estimate composition 3
1.2.3 Sampling for cover information 4
1.2.4 How many trees in Sweden? 4
1.3 Probability sample 5
1.3.1 Selection probability of a sample 5
1.3.2 Inclusion probability 7
1.3.3 Sampling frame 8
1.4 Inference 9
1.5 Population descriptive parameters 10
1.5.1 Discrete populations 10
1.5.2 Continuous populations 12
1.6 Historical note 13
1.7 Terms to remember 14
1.8 Appendix 14
1.8.1 Alternative expressions for of 14
2 Sampling Distribution of an Estimator 15
15
18
19
21
24
25
27
27
28
32
32
33
33
2.1 Distribution of values
2.2 Estimation
2.2.1 Consistency
2.2.2 Expected value
2.2.3 Bias
2.2.4 Variance
2.2.5 Standard error
2.2.6 Mean square error
2.3 Interval estimation
2.4 The role of simulated sampling
2.5 Other considerations
2.6 Terms to remember
2.7 Exercises
viii CONTENTS
2.8 Appendix 34
2.8.1 Derivation of the relationship between mean square error.
variance, and squared bias 34
3 Sampling Designs for Discrete Populations 35
3.1 Introduction 35
3.2 Equal probability designs 35
3.2.1 Simple random sampling 35
Simple random sampling without replacement 36
Selecting a SRSwoR sample 42
Simple random sampling with replacement 44
Selecting a SRSwR sample 48
3.2.2 Systematic sampling 49
Circular systematic sampling 56
3.2.3 Bernoulli sampling 57
3.3 Unequal probability designs 61
3.3.1 List sampling 62
Manipulating selection probabilities to increase precision 63
3.3.2 Poisson sampling 68
3.3.3 Unequal probability systematic sampling 71
3.3.4 Rao, Hartley. Cochran sampling strategy 74
3.4 Terms to remember 77
3.5 Exercises 77
3.6 Appendix 79
3.6.1 Factorial and combinatorial notation 79
3.6.2 Derivation of the inclusion probability of an element for
SRSwoR. 79
3.6.3 Proof of unbiasedness of iy„ as an estimator of rv 80
3.6.4 Derivation of V {Ny ] in (3.6) following SRSwoR 81
3.6.5 Proof of unbiasedness of s* as estimator of a* following
SRSwoR 83
3.6.6 Derivation of the inclusion probability of an element for
SRSwR 84
3.6.7 Derivation of E n) and V[n] following Bernoulli
sampling 84
3.6.8 Derivation of the expected value and variance of iyp 85
3.6.9 Proof of the unbiasedness of f [ xyp ] as an estimator of
y [iyp] 89
3.6.10 Variance of estimated proportions 89
3.6.11 Nearly exact confidence intervals for proportions 90
3.6.12 Expected sample size 91
4 Sampling Designs for Continuous Populations 93
4.1 Introduction 93
4.2 Crude Monte Carlo 94
CONTENTS ix
4.2.1 Definitions 95
4.2.2 Selection 97
4.2.3 Estimation 98
4.2.4 Antithetic variâtes 102
4.2.5 Systematic selection 104
4.3 Importance sampling 106
4.3.1 Proxy function 107
4.3.2 Selection by the inverse-transform method 108
4.3.3 Selection by the acceptance-rejection method 109
4.3.4 Estimation 110
4.4 Control variate estimation 114
4.5 Sampling in two or three dimensions 116
4.5.1 Selection of a sample point 117
4.5.2 Estimation 118
4.5.3 Systematic selection 119
4.5.4 Three dimensions 120
4.6 General notation 121
4.7 Terms to remember 121
4.8 Exercises and projects 122
4.9 Appendix 123
4.9.1 Proof of the unbiasedness of rp as an estimator of tp 124
4.9.2 Derivation of V [rp] 125
4.9.3 The Horvitz-Thompson estimator of tp and its variance 126
5 Stratified Sampling Designs 127
5.1 Introduction 127
5.2 Rationale for stratified sampling 127
5.3 Estimation with stratified sampling 129
5.3.1 Notation 129
5.3.2 HT estimation 130
5.3.3 More general estimation 134
5.3.4 Stratified random sampling 137
5.4 Sample allocation among strata 140
5.4.1 Equal allocation 140
5.4.2 Proportional allocation 141
5.4.3 x-Proportional allocation 143
5.4.4 Optimal allocation, equal sampling costs 143
5.4.5 Optimal allocation, unequal sampling costs 145
5.4.6 Power allocation 145
5.4.7 Allocation for multiresource surveys 146
5.4.8 Comparison of allocation rules 147
5.5 Incorrect assignment of population elements into strata 148
5.6 Double sampling for stratification 149
5.7 Poststratification 152
5.7.1 Preliminary details about poststratification 152
x CONTENTS
5.7.2 Poststratification of a SRSwoR sample 153
5.7.3 Poststratification of samples other than SRSwoR 155
5.8 Stratified sampling of a continuous population 156
5.8.1 Probability densities 158
5.8.2 Estimation 158
5.8.3 Sample allocation 161
5.9 Terms to Remember 162
5.10 Exercises 162
5.11 Appendix 162
5.11.1 Proof of design-unbiasedness of rv pst/,. 162
5.11.2 Double sampling for stratification from Resource
Inventory Notes (Frayer 1978) 163
6 Using Auxiliary Information to Improve Estimation 165
6.1 Generalized ratio estimator 166
6.2 Bias of the generalized ratio estimator 169
6.3 Variance of the generalized ratio estimator 171
6.4 Estimated variance of the generalized ratio estimator 176
6.5 Confidence interval estimation 179
6.6 Ratio estimation with systematic sampling design 179
6.7 Generalized ratio estimation with stratified sampling 180
6.7.1 Ratio estimation of population and strata totals 180
6.7.2 Estimating the variances of ry7r,st,sm and r^^crat 183
6.7.3 Ratio estimation of population and strata means 184
6.8 Generalized regression estimator 185
6.8.1 Regression estimation following SRSwoR 186
6.8.2 Regression estimation following any sampling design 189
6.9 Double sampling with ratio and regression estimation 192
6.10 Terms to Remember 198
6.11 Exercises 198
6.12 Appendix 201
6.12.1 Linear correlation coefficient 201
6.12.2 The jackknife estimator of Ry x. 203
6.12.3 Equivalent expression of Bn 204
6.12.4 Joint inclusion probability under unequal probability
systematic sampling 204
7 Sampling with Fixed Area Plots 207
7.1 Introduction 207
7.2 Notation 208
7.2.1 Selection and installation 209
7.3 Sampling protocol 209
7.4 Estimation 210
7.4.1 Inclusion zone of an element 210
7.4.2 Estimation following plot sampling 215
CONTENTS xi
7.4.3 Prorating estimates to unit area values 219
7.4.4 Estimating the mean attribute per element 222
7.4.5 Stratification 222
7.4.6 Sampling intensity 223
7.4.7 Elements near the plot border 223
7.5 Edge effect 223
7.5.1 External peripheral zone 224
7.5.2 Pullback method 225
7.5.3 Grosenbaugh s method 226
7.5.4 Mirage method 227
7.5.5 Walkthrough method 229
7.5.6 Edge corrections for plot clusters 231
Vectorwalk method 232
Reflection method 233
7.6 Plot size and shape 234
7.7 Estimating change 237
7.8 Terms to remember 242
7.9 Exercises 242
7.10 Appendix 246
7.10.1 Joint inclusion zones 246
8 Bitterlich Sampling 247
8.1 Introduction 247
8.2 Fundamental concepts 247
8.2.1 Limiting distance for inclusion 248
8.2.2 Basal area factor 249
8.2.3 Plot radius factor 249
8.2.4 Sampling protocol 250
8.2.5 Bitterlich sampling with English units 253
8.2.6 Noncircular tree boles 253
8.2.7 Expected number of trees selected at a point 254
8.3 Estimation following Bitterlich sampling 254
8.3.1 Estimating xy 254
8.3.2 Estimating basal area 255
8.3.3 Estimating population size 257
8.3.4 Estimating ßy 257
8.3.5 Variances and variance estimators 257
8.3.6 Product estimator 258
8.4 Edge effect 262
8.5 Double sampling 262
8.5.1 Double sampling with second-phase subset of sample
points 263
8.5.2 Optimal allocation 268
8.5.3 Double sampling with a second-phase subset of trees 268
Riff RAP namnlino 268
xii CONTENTS
Subsampling trees with probability proportional to height 269
8.6 Sampling to estimate change in stock 270
8.6.1 Conventional components of change 271
8.6.2 Eriksson s components of change 273
8.7 Terms to remember 275
8.8 Exercises 276
9 Line Intersect Sampling 279
9.1 Introduction 279
9.2 LIS with straight-line transects 280
9.2.1 Sampling protocol 280
9.2.2 Estimation conditioned on transect orientation 283
9.2.3 Unconditional estimation 285
9.2.4 Estimator variance and variance estimators 288
9.2.5 Interval estimation 289
9.2.6 Conditional vs. unconditional estimation 289
9.3 Unit area estimators 290
9.4 Estimation with an auxiliary variate 293
9.5 Estimating the mean attribute 298
9.6 Nesting transects of different lengths 299
9.7 Dealing with edge effect in LIS 299
9.7.1 Walkback method 299
9.7.2 Reflection method 300
9.8 Transects with multiple segments 301
9.8.1 Radial and polygonal transects 302
9.8.2 Sampling protocol for transects having multiple segments 303
9.8.3 Estimation from transects having multiple segments 304
9.8.4 Averaging estimators for straight transects 307
9.9 Parallel transects of uneven length 307
9.10 Terms to remember 309
9.11 Exercises 309
9.12 Appendix 310
9.12.1 Joint inclusion zones 310
9.12.2 Derivation of E[tksqk(0s) 9S] 310
9.12.3 Variance of conditional estimator of xy with auxiliary
variate using transects with a single segment 311
9.12.4 Variance of unconditional estimator of xy with auxiliary
variate using transects with a single segment 311
9.12.5 Conditional expected value and variance of tks, with
transects having multiple segments 311
9.12.6 Unconditional expected value and variance of ^x. with
transects having multiple segments 314
9.12.7 Variance of ïfms 315
9.12.8 Variance of x»ms 317
9.12.9 Variance of T^ 318
CONTENTS xiii
9.12.10 Variance of r^qs 324
10 A Monte Carlo Integration Approach to Areal Sampling 327
10.1 Areal sampling 328
10.1.1 Selection 329
10.1.2 Estimation 330
10.2 Plot sampling 331
10.2.1 Cluster plots 332
10.3 Bitterlich sampling 333
10.4 Point relascope sampling 334
10.5 Line intersect sampling 336
10.5.1 Unconditional estimation 338
10.6 Perpendicular distance sampling 339
10.6.1 Omnibus PDS 341
Coverage area 342
10.7 Edge correction 343
343
344
344
346
348
349
351
10.10 Exercises 351
10.11 Appendix 351
10.11.1 Variance of rp,rep 351
10.11.2 Variance with edge correction by walkthrough or mirage 353
10.11.3 LIS with segmented transects and correction of edge
effect 354
11 Miscellaneous Methods 357
11.1 Introduction 357
11.2 Point relascope sampling 357
11.3 Horizontal line sampling 359
11.3.1 Sausage sampling 361
11.3.2 Modified sausage samping 362
11.3.3 Redux: LIS 363
11.4 Transect relascope sampling 364
11.4.1 Stâhl s method 366
11.5 Ranked set sampling 367
11.5.1 Overview 368
11.5.2 Traditional applications 369
Estimation 370
11.5.3 Discrete applications 371
Efficiency 372
10.7.1 Buffer method
10.7.2 Direct measurement of inclusion area
10.7.3 Mirage method
10.7.4 Reflection method for transects
10.7.5 Walkthrough method
10.8 Redux : Continuous versus discrete
10.9 Terms to Remember
xiv CONTENTS
11.6 Adaptive cluster sampling 373
11.6.1 Sampling tessellated landscapes 373
11.6.2 Selection and Estimation 376
Probability proportional to area 376
Probability proportional to number of plots 377
Selection of plots without replacement 377
11.6.3 Sampling landscapes without tessellation 378
Estimation with network inclusion probabilities 379
Estimation with element inclusion probabilities 380
Edge effect 381
11.7 3P sampling 382
11.7.1 Selection 382
11.7.2 Variance estimation following 3P sampling 385
11.7.3 Regression adjustment of inclusion probabilities 387
11.7.4 Composite and calibration estimation 388
11.8 Terms to Remember 388
11.9 Exercises 389
11.10 Appendix 390
11.10.1 Details on 3P sampling 390
12 Two-stage Sampling 393
12.1 Customary two-stage sampling 394
12.1.1 Estimating cluster totals 394
12.1.2 Estimating the population total from cluster totals 395
12.1.3 SRSwoR special case 397
12.1.4 Self-weighting SRSwoR designs 398
12.1.5 Ppswr special case 398
12.1.6 Examples 398
12.1.7 Alternative estimators 399
12.2 General two-stage sampling 400
12.3 Three-stage sampling 402
12.4 Terms to Remember 404
13 Randomized Branch Sampling 405
13.1 Terminology 405
13.2 Path selection 406
13.3 Estimation 409
13.3.1 Average stem length 411
13.4 Selection probabilities 412
13.5 Tools and tricks of the trade 414
13.6 Subsampling a path 415
13.6.1 Subsampling strategy 415
13.6.2 Crude Monte Carlo 416
13.6.3 Importance sampling 417
13.6.4 Constructing a proxy function 417
CONTENTS xv
13.6.5 Sampling with a control variate 419
13.6.6 Choice of method 420
13.7 Terms to remember 420
13.8 Exercises and projects 421
13.9 Appendix 13 421
13.9J Proof of the unbiasedness of ryQi 421
14 Sampling with Partial Replacement 423
14.1 Introduction 423
14.2 Estimation with partially replaced sampling units 424
14.2.1 Optimal number of remeasured units 429
14.2.2 Estimation of xy tj) with estimated parameter values 429
14.2.3 Contribution of remeasured sample units 431
14.3 Estimation of change 431
14.3.1 Optimal estimator 432
14.3.2 Additive estimator 432
14.3.3 Change estimator based on remeasured sampling
locations 432
14.4 SPR with stratification 433
14.5 SPR for three occasions 433
14.6 Concluding remarks 434
14.7 Terms to remember 435
14.8 Appendix 435
14.8.1 Derivation of the composite estimator 435
14.8.2 Variance of the composite estimator 436
14.8.3 Components of the composite estimator ry,spR(f3 : h ) 437
Bibliography 439
Author Index 459
Subject Index 467
|
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| author | Gregoire, Timothy G. Valentine, Harry T. |
| author_facet | Gregoire, Timothy G. Valentine, Harry T. |
| author_role | aut aut |
| author_sort | Gregoire, Timothy G. |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 577 - Ecology |
| dewey-raw | 577.072/3 |
| dewey-search | 577.072/3 |
| dewey-sort | 3577.072 13 |
| dewey-tens | 570 - Biology |
| discipline | Biologie Geographie |
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| id | DE-604.BV019985709 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T12:09:35Z |
| institution | BVB |
| isbn | 9781584883708 1584883707 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013307706 |
| oclc_num | 123968463 |
| open_access_boolean | |
| owner | DE-M49 DE-BY-TUM DE-634 |
| owner_facet | DE-M49 DE-BY-TUM DE-634 |
| physical | XX, 474 S. graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Chapman & Hall/CRC |
| record_format | marc |
| spellingShingle | Gregoire, Timothy G. Valentine, Harry T. Sampling strategies for natural resources and the environment Sciences de l'environnement - Méthodes statistiques Échantillonnage (Écologie) Environmental sampling Environmental sciences Statistical methods Umweltanalytik (DE-588)4282985-9 gnd Statistik (DE-588)4056995-0 gnd Umweltdaten (DE-588)4452653-2 gnd Stichprobennahme (DE-588)4183250-4 gnd Ökologie (DE-588)4043207-5 gnd Natürliche Ressourcen (DE-588)4075236-7 gnd Datenerhebung (DE-588)4155272-6 gnd |
| subject_GND | (DE-588)4282985-9 (DE-588)4056995-0 (DE-588)4452653-2 (DE-588)4183250-4 (DE-588)4043207-5 (DE-588)4075236-7 (DE-588)4155272-6 |
| title | Sampling strategies for natural resources and the environment |
| title_alt | Sampling techniques for natural and environmental resources |
| title_auth | Sampling strategies for natural resources and the environment |
| title_exact_search | Sampling strategies for natural resources and the environment |
| title_full | Sampling strategies for natural resources and the environment Timothy G. Gregoire ; Harry T. Valentine |
| title_fullStr | Sampling strategies for natural resources and the environment Timothy G. Gregoire ; Harry T. Valentine |
| title_full_unstemmed | Sampling strategies for natural resources and the environment Timothy G. Gregoire ; Harry T. Valentine |
| title_short | Sampling strategies for natural resources and the environment |
| title_sort | sampling strategies for natural resources and the environment |
| topic | Sciences de l'environnement - Méthodes statistiques Échantillonnage (Écologie) Environmental sampling Environmental sciences Statistical methods Umweltanalytik (DE-588)4282985-9 gnd Statistik (DE-588)4056995-0 gnd Umweltdaten (DE-588)4452653-2 gnd Stichprobennahme (DE-588)4183250-4 gnd Ökologie (DE-588)4043207-5 gnd Natürliche Ressourcen (DE-588)4075236-7 gnd Datenerhebung (DE-588)4155272-6 gnd |
| topic_facet | Sciences de l'environnement - Méthodes statistiques Échantillonnage (Écologie) Environmental sampling Environmental sciences Statistical methods Umweltanalytik Statistik Umweltdaten Stichprobennahme Ökologie Natürliche Ressourcen Datenerhebung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=013307706&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT gregoiretimothyg samplingstrategiesfornaturalresourcesandtheenvironment AT valentineharryt samplingstrategiesfornaturalresourcesandtheenvironment AT gregoiretimothyg samplingtechniquesfornaturalandenvironmentalresources AT valentineharryt samplingtechniquesfornaturalandenvironmentalresources |
Inhaltsverzeichnis
Paper/Kapitel scannen lassen
Paper/Kapitel scannen lassen
Teilbibliothek Weihenstephan
| Signatur: |
1002 UMW 002 2007 A 6918
Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |