Finite population sampling and inference: a prediction approach
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Wiley
2000
|
| Series: | Wiley series in probability and statistics
Wiley interscience |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVII, 504 S. |
| ISBN: | 0471293415 |
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| 245 | 1 | 0 | |a Finite population sampling and inference |b a prediction approach |c Richard Valliant ; Alan H. Dorfman ; Richard M. Royall |
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Record in the Search Index
| _version_ | 1804128033771094016 |
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| adam_text | IMAGE 1
FINITE POPULATION SAMPLING
AND INFERENCE A PREDICTION APPROACH RICHARD VALLIANT ALAN H. DORFMAN
RICHARD M. ROYALL
A WILEY-INTERSCIENCE PUBLICATION JOHN WILEY & SONS, INC. NEW YORK *
CHICHESTER * WEINHEIM * BRISBANE * SINGAPORE * TORONTO
IMAGE 2
CONTENTS
PREFACE 1. INTRODUCTION TO PREDICTION THEORY
1.1 SAMPLING THEORY AND THE REST OF STATISTICS, 1 1.2 PREDICTION THEORY,
2 1.3 PROBABILITY SAMPLING THEORY, 7 1.3.1 TECHNIQUES USED IN
PROBABILITY SAMPLING, 9
1.3.2 SOME MATHEMATICAL DETAILS, 11 1.4 WHICH APPROACH TO USE?, 14 1.5
WHY USE RANDOM SAMPLING?, 19 EXERCISES, 22
2. PREDICTION THEORY UNDER THE GENERAL LINEAR MODEL
2.1 DEFINITIONS AND A SIMPLE EXAMPLE, 26 2.2 GENERAL PREDICTION THEOREM,
29 2.3 AELC/PREDICTOR UNDER SOME SIMPLE MODELS, 31 2.4 UNIT WEIGHTS, 32
2.5* ASYMPTOTIC NORMALITY OF THE BLU PREDICTOR, 34
2.6 IGNORABLE AND NONIGNORABLE SAMPLE SELECTION METHODS, 35 2.6.1
EXAMPLES, 36 2.6.2* FORMAL DEFINITION OF IGNORABLE SELECTION, 36
2.7* COMPARISONS WITH DESIGN-BASED REGRESSION ESTIMATION, 40 EXERCISES,
44
3. BIAS-ROBUSTNESS
3.1 DESIGN AND BIAS, 50 3.2 POLYNOMIAL FRAMEWORK AND BALANCED SAMPLES,
53
IMAGE 3
VUEI CONTENTS
3.2.1 EXPANSION ESTIMATOR AND BALANCED SAMPLES, 54
3.2.2* ORDER OF THE BIAS OF THE EXPANSION ESTIMATOR, 55 3.2.3 RATIO
ESTIMATOR AND BALANCED SAMPLES, 55 3.2.4 BIAS-ROBUST STRATEGIES, 56
3.2.5 SIMULATION STUDY TO ILLUSTRATE CONDITIONAL BIASES
AND MEAN SQUARED ERRORS, 57 3.2.6 BALANCE AND MULTIPLE Y VARIABLES, 59
3.3 WEIGHTED BALANCE, 61 3.3.1 ELEMENTARY ESTIMATORS UNBIASED UNDER
WEIGHTED BALANCE, 62 3.3.2 BLU ESTIMATORS AND WEIGHTED BALANCE, 63 3.4
METHODS OF SELECTING BALANCED SAMPLES, 65 3.4.1 SIMPLE RANDOM SAMPLING,
66
3.4.2 SYSTEMATIC EQUAL PROBABILITY SAMPLING, 67 3.4.3 STRATIFICATION
BASED ON THE AUXILIARY, 68 3.4.4 RESTRICTED RANDOM SAMPLING, 71 3.4.5
SAMPLING FOR WEIGHTED BALANCE, 72
3.4.6 RESTRICTED PPS SAMPLING, 74 3.4.7 PARTIAL BALANCING, 77 3.5
SIMULATION STUDY OF WEIGHTED BALANCE, 77 3.5.1 RESULTS USING THE
HOSPITALS POPULATION, 78
3.5.2 INTERACTION OF MODEL SPECIFICATION WITH SAMPLE CONFIGURATION, 82
3.6 SUMMARY, 85 3.7 ROBUSTNESS AND DESIGN-BASED INFERENCE, 85
EXERCISES, 90
4. ROBUSTNESS AND EFFICIENCY 95
4.1 INTRODUCTION, 95 4.2 GENERAL LINEAR MODEL, 96 4.2.1 BLU PREDICTOR
UNDER THE GENERAL LINEAR MODEL WITH DIAGONAL VARIANCE MATRIX, 97
4.2.2 EXAMPLES OF MINIMAL MODELS, 101 4.3 COMPARISONS USING AN
ARTIFICIAL POPULATION, 103 4.3.1 RESULTS FOR PROBABILITY PROPORTIONAL TO
X SAMPLING AND X-BALANCE, 105
4.3.2 RESULTS FOR PROBABILITY PROPORTIONAL TO X 1/2 SAMPLING AND X 1/2
-BALANCE, 107
4.3.3 RESULTS FOR EQUAL PROBABILITY SYSTEMATIC SAMPLING AND SIMPLE
BALANCE, 110
IMAGE 4
4.4 SAMPLE SIZE DETERMINATION, 114
4.5 SUMMARY AND PERSPECTIVE, 118 4.6* REMARKS ON DESIGN-BASED INFERENCE,
119 EXERCISES, 122 VARIANCE ESTIMATION
5.1 EXAMPLES OF ROBUST VARIANCE ESTIMATION, 127 5.1.1 HOMOSCEDASTIC
THROUGH THE ORIGIN MODEL, 127 5.1.2 VARIANCE ESTIMATORS FOR THE RATIO
ESTIMATOR, 130
5.2 VARIANCE ESTIMATION OF A LINEAR FUNCTION OF THE PARAMETER, 5.3
SANDWICH ESTIMATOR OF VARIANCE, 135 5.3.1 CONSISTENCY OF V R , 136 5.3.2
SOME COMMENTS ON THE REQUIREMENTS FOR
CONSISTENCY OF THE SANDWICH ESTIMATOR, 138 5.4 VARIANTS ON THE BASIC
ROBUST VARIANCE ESTIMATOR, 139 5.4.1 INTERNAL AND EXTERNAL ADJUSTMENTS
TO THE SANDWICH ESTIMATOR, 139
5.4.2 JACKKNIFE VARIANCE ESTIMATOR, 141 5.5 VARIANCE ESTIMATION FOR
TOTAIS, 144 5.5.1 SOME SIMPLE EXAMPLES, 146
5.5.2 EFFECT OF A LARGE SAMPLING FRACTION, 149 5.6 MISSPECIFICATION OF
THE REGRESSION COMPONENT, 149 5.7 HIDDEN REGRESSION COMPONENTS, 152
5.7.1 SOME ARTIFICIAL EXAMPLES, 153 5.7.2 COUNTIES 70 POPULATION, 157
5.7.3 LURKING DISCRETE SKEWED VARIABLES, 161 5.8 COMPARISONS WITH
DESIGN-BASED VARIANCE ESTIMATION, 161 EXERCISES, 164
STRATIFIED POPULATIONS
6.1 STRATIFICATION WITH HOMOGENEOUS SUBPOPULATIONS, 168 6.2 STRATIFIED
LINEAR MODEL AND WEIGHTED BALANCED SAMPLES, 173 6.2.1 OPTIMAL ALLOCATION
FOR STRATIFIED BALANCED
SAMPLING, 174 6.2.2 CASE OF A SINGLE MODEL FOR THE POPULATION, 175 6.2.3
CASE OF A SINGLE AUXILIARY VARIABLE, 177 6.3 SAMPLING FRACTIONS GREATER
THAN 1, 179 6.4 ALLOCATION TO STRATA IN MORE COMPLICATED CASES, 181
6.4.1 CONTRASTS BETWEEN STRATA, 182 6.4.2 MORE THAN ONE TARGET VARIABLE,
184
IMAGE 5
X
CONTENTS
6.5 TWO TRADITIONAL TOPICS, 186
6.5.1 EFFICIENCY OF THE SEPARATE RATIO ESTIMATOR, 186 6.5.2 FORMATION OF
STRATA, 189 6.6 SOME EMPIRICAL RESULTS ON STRATA FORMATION, 192 6.7
VARIANCE ESTIMATION IN STRATIFIED POPULATIONS, 197
6.8 STRATIFICATION IN DESIGN-BASED THEORY, 200 EXERCISES, 205
7. MODELS WITH QUALITATIVE AUXILIARIES 211
7.1 SIMPLE EXAMPLE, 211 7.2 FACTORS, LEVELS, AND EFFECTS, 213 7.3
GENERALIZED INVERSES, 214
7.4 ESTIMATING LINEAR COMBINATIONS OF THE Y S, 217 7.5 ONE-WAY
CLASSIFICATION, 220 7.6 TWO-WAY NESTED CLASSIFICATION, 223 7.7 TWO-WAY
CLASSIFICATION WITHOUT INTERACTION, 225
7.8 TWO-WAY CLASSIFICATION WITH INTERACTION, 226 7.9 COMBINING
QUALITATIVE AND QUANTITATIVE AUXILIARIES, 231 7.9.1 GENERAL COVARIANCE
MODEL, 232 7.9.2 ONE-WAY CLASSIFICATION WITH A SINGLE COVARIATE, 234
7.9.3 EXAMPLES, 235 7.10 VARIANCE ESTIMATION, 237 7.10.1 BASIC ROBUST
ALTERNATIVES, 238 7.10.2 JACKKNIFE VARIANCE ESTIMATOR, 240 EXERCISES,
242
8. CLUSTERED POPULATIONS 246
8.1 INTRACLUSTER CORRELATION MODEL FOR A CLUSTERED POPULATION, 247 8.1.1
DISCUSSION OF THE COMMON MEAN MODEL, 248 8.1.2 SIMPLE SAMPLE DESIGNS,
249 8.2 CLASS OF UNBIASED ESTIMATORS UNDER THE COMMON
MEAN MODEL, 250 8.2.1 ONE-STAGE CLUSTER SAMPLING, 252 8.2.2 BLU
PREDICTOR, 254 8.2.3 VARIANCE COMPONENT MODEL, 256 8.3 ESTIMATION OF
PARAMETERS IN THE CONSTANT PARAMETER
MODEL, 257 8.3.1 ANOVA ESTIMATORS, 257 8.3.2* MAXIMUM LIKELIHOOD
ESTIMATORS, 258
IMAGE 6
CONTENTS
XI
8.3.3* LOWER BOUND ON THE INTRACLUSTER CORRELATION, 261 8.4 SIMULATION
STUDY FOR THE COMMON MEAN MODEL, 261 8.5 BIASES OF COMMON MEAN
ESTIMATORS UNDER
A MORE GENERAL MODEL, 264 8.6 ESTIMATION UNDER A MORE GENERAL REGRESSION
MODEL, 266 8.7* ROBUSTNESS AND OPTIMALITY, 271 8.8 EFFICIENT DESIGN FOR
THE COMMON MEAN MODEL, 275
8.8.1 CHOOSING THE SET OF SAMPLE CLUSTERS FOR THE BLU ESTIMATOR, 275
8.8.2 CHOOSING THE SET OF SAMPLE CLUSTERS FOR THE UNBIASED ESTIMATORS,
276 8.8.3 OPTIMAL ALLOCATION OF SECOND-STAGE UNITS GIVEN
A FIXED SET OF FIRST-STAGE SAMPLE UNITS, 277 8.8.4 OPTIMAL FIRST AND
SECOND-STAGE ALLOCATION CONSIDERING COSTS, 279 8.9* ESTIMATION WHEN
CLUSTER SIZES ARE UNKNOWN, 283 8.10 TWO-STAGE SAMPLING IN DESIGN-BASED
PRACTICE, 287 EXERCISES, 290
9. ROBUST VARIANCE ESTIMATION IN TWO-STAGE CLUSTER SAMPLING 296
9.1 COMMON MEAN MODEL AND A GENERAL CLASS OF VARIANCE ESTIMATORS, 296
9.2* OTHER VARIANCE ESTIMATORS, 299 9.2.1* NON-ROBUST ANOVA ESTIMATOR,
300
9.2.2* ALTERNATIVE ROBUST VARIANCE ESTIMATORS, 301 9.3 EXAMPLES OF THE
VARIANCE ESTIMATORS, 305 9.3.1 RATIO ESTIMATOR, 305 9.3.2 MEAN OF RATIOS
ESTIMATOR, 307
9.3.3 NUMERICAL ILLUSTRATIONS, 307 9.4* VARIANCE ESTIMATION FOR AN
ESTIMATED TOTAL - UNKNOWN CLUSTER SIZES, 309 9.5 REGRESSION ESTIMATOR,
310
9.5.1 SANDWICH VARIANCE ESTIMATOR, 311 9.5.2 ADJUSTMENTS TO THE SANDWICH
ESTIMATOR, 313 9.5.3 JACKKNIFE ESTIMATOR, 314 9.6 COMPARISONS OF
VARIANCE ESTIMATORS IN A SIMULATION
STUDY, 318 EXERCISES, 320 10. ALTERNATIVE VARIANCE ESTIMATION METHODS
323
10.1 ESTIMATING THE VARIANCE OF ESTIMATORS OF NONLINEAR
IMAGE 7
CONTENTS XI
8.3.3* LOWER BOUND ON THE INTRACLUSTER CORRELATION, 261 8.4 SIMULATION
STUDY FOR THE COMMON MEAN MODEL, 261 8.5 BIASES OF COMMON MEAN
ESTIMATORS UNDER A MORE GENERAL MODEL, 264 8.6 ESTIMATION UNDER A MORE
GENERAL REGRESSION MODEL, 266 8.7* ROBUSTNESS AND OPTIMALITY, 271 8.8
EFFICIENT DESIGN FOR THE COMMON MEAN MODEL, 275
8.8.1 CHOOSING THE SET OF SAMPLE CLUSTERS FOR THE 2?L/ESTIMATOR, 275
8.8.2 CHOOSING THE SET OF SAMPLE CLUSTERS FOR THE UNBIASED ESTIMATORS,
276 8.8.3 OPTIMAL ALLOCATION OF SECOND-STAGE UNITS GIVEN
A FIXED SET OF FIRST-STAGE SAMPLE UNITS, 277 8.8.4 OPTIMAL FIRST AND
SECOND-STAGE ALLOCATION CONSIDERING COSTS, 279 8.9* ESTIMATION WHEN
CLUSTER SIZES ARE UNKNOWN, 283 8.10 TWO-STAGE SAMPLING IN DESIGN-BASED
PRACTICE, 287 EXERCISES, 290
9. ROBUST VARIANCE ESTIMATION IN TWO-STAGE CLUSTER SAMPLING 296
9.1 COMMON MEAN MODEL AND A GENERAL CLASS OF VARIANCE ESTIMATORS, 296
9.2* OTHER VARIANCE ESTIMATORS, 299 9.2.1* NON-ROBUST ANOVA ESTIMATOR,
300
9.2.2* ALTERNATIVE ROBUST VARIANCE ESTIMATORS, 301 9.3 EXAMPLES OF THE
VARIANCE ESTIMATORS, 305 9.3.1 RATIO ESTIMATOR, 305
9.3.2 MEAN OF RATIOS ESTIMATOR, 307 9.3.3 NUMERICAL ULUSTRATIONS, 307
9.4* VARIANCE ESTIMATION FOR AN ESTIMATED TOTAL - UNKNOWN CLUSTER SIZES,
309
9.5 REGRESSION ESTIMATOR, 310 9.5.1 SANDWICH VARIANCE ESTIMATOR, 311
9.5.2 ADJUSTMENTS TO THE SANDWICH ESTIMATOR, 313 9.5.3 JACKKNIFE
ESTIMATOR, 314 9.6 COMPARISONS OF VARIANCE ESTIMATORS IN A SIMULATION
STUDY, 318 EXERCISES, 320 10. ALTERNATIVE VARIANCE ESTIMATION METHODS
323
10.1 ESTIMATING THE VARIANCE OF ESTIMATORS OF NONLINEAR
IMAGE 8
CONTENTS
FUNCTIONS, 323
10.1.1 VARIANCE ESTIMATION FOR A RATIO OF ESTIMATED TOTAIS, 326 10.1.2
JACKKNIFE AND NONLINEAR FUNCTIONS, 329 10.2 BALANCED HALF-SAMPLE
VARIANCE ESTIMATION, 330
10.2.1 APPLICATION TO THE STRATIFIED EXPANSION ESTIMATOR, 331 10.2.2
ORTHOGONAL ARRAYS, 333 10.2.3 EXTENSION TO NONLINEAR FUNCTIONS, 334
10.2.4 TWO-STAGE SAMPLING, 336 10.2.5 OTHER FORMS OF THE BHS VARIANCE
ESTIMATOR, 340 10.2.6 PARTIALLY BALANCED HALF-SAMPLING, 341
10.2.7 DESIGN-BASED PROPERTIES, 344 10.3 GENERALIZED VARIANCE FUNCTIONS,
344 10.3.1 SOME THEORY FOR GVFS, 345 10.3.2 ESTIMATION OF GVF
PARAMETERS, 347 EXERCISES, 348
SPECIAL TOPICS AND OPEN QUESTIONS 351
11.1 ESTIMATION IN THE PRESENCE OF OUTLIERS, 352 11.1.1 GROSS ERROR
MODEL, 354 11.1.2 SIMPLE REGRESSION MODEL, 361 11.1.3 AREAS FOR
RESEARCH, 366 11.2 NONLINEAR MODELS, 367
11.2.1 MODEL FOR BERNOULLI RANDOM VARIABLES, 370 11.2.2 AREAS FOR
RESEARCH, 372 11.3 NONPARAMETRIC ESTIMATION OF TOTAIS, 372 11.3.1
NONPARAMETRIC REGRESSION FOR TOTAIS, 373
11.3.2 NONPARAMETRIC CALIBRATION ESTIMATION, 375 11.4 DISTRIBUTION
FUNCTION AND QUANTILE ESTIMATION, 377 11.4.1 ESTIMATION UNDER
HOMOGENEOUS AND STRATIFIED MODELS, 380
11.4.2 ESTIMATION OFF^-) UNDER A REGRESSION MODEL, 382 11.4.3 LARGE
SAMPLE PROPERTIES, 387 11.4.4 THE EFFECT OF MODEL MISSPECIFICATION, 388
11.4.5 DESIGN-BASED APPROACHES, 390 11.4.6 NONPARAMETRIC
REGRESSION-BASED ESTIMATORS, 391 11.4.7 SOME OPEN QUESTIONS, 393 11.5
SMALL AREA ESTIMATION, 394
IMAGE 9
CONTENTS
XUEI
11.5.1 ESTIMATION WHEN CELL MEANS ARE UNRELATED, 395 11.5.2 CELL MEANS
DETERMINED BY CLASS BUT UNCORRELATED, 396 11.5.3 SYNTHETIC AND COMPOSITE
ESTIMATORS, 400 11.5.4 USING AUXILIARY DATA, 402
11.5.5 AUXILIARY DATA AT THE CELL LEVEL, 404 11.5.6 NEED FOR A SMALL
AREA ESTIMATION CANON, 406 EXERCISES, 407
APPENDIX A. SOME BASIC TOOLS 413
A.L ORDERS OF MAGNITUDE, 0( *) AND O( *), 413 A.2 CONVERGENCE IN
PROBABILITY AND IN DISTRIBUTION, 413 A.3 PROBABILISTIC ORDERS OF
MAGNITUDE, O P () AND O P (-), 414 A.4 CHEBYSHEV S INEQUALITY, 414
A.5 CAUCHY-SCHWARZ INEQUALITY, 414 A.6 SLUTSKY S THEOREM, 414 A.7
TAYLOR S THEOREM, 415 A.7.1 UNIVARIATE VERSION, 415
A.7.2 MULTIVARIATE VERSION, 415 A.8 CENTRAL LIMIT THEOREMS FOR
INDEPENDENT, NOT IDENTICALLY DISTRIBUTED RANDOM VARIABLES, 415 A.9
CENTRAL LIMIT THEOREM FOR SIMPLE RANDOM SAMPLING, 416
A.10 GENERALIZED INVERSE OF A MATRIX, 417 APPENDIX B. DATASETS 420
B.L CANCER POPULATION, 422 B.2 HOSPITALS POPULATION, 424 B.3 COUNTIES 60
POPULATION, 428 B.4 COUNTIES 70 POPULATION, 431 B.5 LABOR FORCE
POPULATION, 434 B.6 THIRD GRADE POPULATION, 444
APPENDIX C. S-PLUS FUNCTIONS 446
BIBLIOGRAPHY 460
ANSWERS TO SELECT EXERCISES 474
AUTHOR INDEX 484
SUBJECT INDEX 488
|
| any_adam_object | 1 |
| author | Valliant, Richard 1950- |
| author_GND | (DE-588)170604675 (DE-588)171032551 (DE-588)170562549 |
| author_facet | Valliant, Richard 1950- |
| author_role | aut |
| author_sort | Valliant, Richard 1950- |
| author_variant | r v rv |
| building | Verbundindex |
| bvnumber | BV013267616 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
| callnumber-raw | QA276.6 |
| callnumber-search | QA276.6 |
| callnumber-sort | QA 3276.6 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | QH 235 |
| ctrlnum | (OCoLC)43567494 (DE-599)BVBBV013267616 |
| dewey-full | 519.5/2 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/2 |
| dewey-search | 519.5/2 |
| dewey-sort | 3519.5 12 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV013267616 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T18:42:49Z |
| institution | BVB |
| isbn | 0471293415 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009045280 |
| oclc_num | 43567494 |
| open_access_boolean | |
| owner | DE-N2 DE-945 DE-19 DE-BY-UBM |
| owner_facet | DE-N2 DE-945 DE-19 DE-BY-UBM |
| physical | XVII, 504 S. |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Wiley |
| record_format | marc |
| series2 | Wiley series in probability and statistics Wiley interscience |
| spelling | Valliant, Richard 1950- Verfasser (DE-588)170604675 aut Finite population sampling and inference a prediction approach Richard Valliant ; Alan H. Dorfman ; Richard M. Royall New York [u.a.] Wiley 2000 XVII, 504 S. txt rdacontent n rdamedia nc rdacarrier Wiley series in probability and statistics Wiley interscience Prévision, Théorie de la Steekproeven gtt Waarschijnlijkheid (statistiek) gtt Échantillonnage (Statistique) Statistik Prediction theory Sampling (Statistics) Sampling Studies Statistics methods Bevölkerungsstatistik (DE-588)4006298-3 gnd rswk-swf Stichprobe (DE-588)4057502-0 gnd rswk-swf Bevölkerungsstatistik (DE-588)4006298-3 s Stichprobe (DE-588)4057502-0 s DE-604 Dorfman, Alan H. Sonstige (DE-588)171032551 oth Royall, R. M. Sonstige (DE-588)170562549 oth GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009045280&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Valliant, Richard 1950- Finite population sampling and inference a prediction approach Prévision, Théorie de la Steekproeven gtt Waarschijnlijkheid (statistiek) gtt Échantillonnage (Statistique) Statistik Prediction theory Sampling (Statistics) Sampling Studies Statistics methods Bevölkerungsstatistik (DE-588)4006298-3 gnd Stichprobe (DE-588)4057502-0 gnd |
| subject_GND | (DE-588)4006298-3 (DE-588)4057502-0 |
| title | Finite population sampling and inference a prediction approach |
| title_auth | Finite population sampling and inference a prediction approach |
| title_exact_search | Finite population sampling and inference a prediction approach |
| title_full | Finite population sampling and inference a prediction approach Richard Valliant ; Alan H. Dorfman ; Richard M. Royall |
| title_fullStr | Finite population sampling and inference a prediction approach Richard Valliant ; Alan H. Dorfman ; Richard M. Royall |
| title_full_unstemmed | Finite population sampling and inference a prediction approach Richard Valliant ; Alan H. Dorfman ; Richard M. Royall |
| title_short | Finite population sampling and inference |
| title_sort | finite population sampling and inference a prediction approach |
| title_sub | a prediction approach |
| topic | Prévision, Théorie de la Steekproeven gtt Waarschijnlijkheid (statistiek) gtt Échantillonnage (Statistique) Statistik Prediction theory Sampling (Statistics) Sampling Studies Statistics methods Bevölkerungsstatistik (DE-588)4006298-3 gnd Stichprobe (DE-588)4057502-0 gnd |
| topic_facet | Prévision, Théorie de la Steekproeven Waarschijnlijkheid (statistiek) Échantillonnage (Statistique) Statistik Prediction theory Sampling (Statistics) Sampling Studies Statistics methods Bevölkerungsstatistik Stichprobe |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009045280&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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