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| Авторизация |
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| Поиск по указателям |
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| Kadane J.B. (ed.) — Robustness of Bayesian Analyses |
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| Предметный указатель |
 -minimax 81
-minimax regret 81 96
 -contamination class 139
-optimal decision 167
Absolute error 170 224
Admissibility 88 99
Admissible 142
Alternative hypothesis 37
Analysis of variance 50
Ancillary statistic 59
Approach, decision-theoretic 66 130
Approximate prior 72
Assumption I 130
Bayes, estimates 266
Bayes, risk 95
Bayes, risk, frequented 85 139 141
Bayesian distribution theory 20
Bayesian methodologically 129
Bayesian procedure 137
Bayes’ Theorem 3 7
Berkeley tradition 138
Bernoulli process 21
Beta distribution 21
Betting paradigms 130
Bound, upper variance 243
Bounded continuous loss 154
Bounded growth loss 156
Bounded uniformly 186 187 190 194 197 200 202 203 206 209 216 217 218 219 220 221
Bounds, symmetrically restricted 257
C-minimax 128
Cauchy distribution 137
Chi-square distribution 49
Classes of prior distribution 73
Classical statistics 3
Coefficient load curve model 278
Coherence 70
Concave function 224
Conditional inference 70
conditional probabilities 7
Confidence levels 5
Confidence procedures 87
Consistency 6 92
Continuous in  uniformly in D 154 169 177 186 187
Convergent uniformly 168 174 177 181
Convex function 225
Credible intervals 25
Critical likelihood ratios 33
Curve, ridge 235
DATA 8
Data analysis 83
Decision procedure 137
Decision-maker 137
Decision-theoretic approach 66 130
Degrees of freedom 138
Density function 8
Density, normal 46
Design of experiments 102
Dichotomy, simple 32
Diffuseness 19
Distance function 168 170 172
Distributed lag, seasonal 292
Distribution, Bayes distribution theory 20
Distribution, Beta 21
Distribution, Cauchy 137
Distribution, chi-square 49
Distribution, classes of prior 73
Distribution, conjugate 21 98
Distribution, joint 24
Distribution, theory 4
Distributions 11
Entropy, maximum 99
Errors 5
Errors, absolute 170 224
Estimate modal 259
Estimate point 25
Estimation, interval 3 25
Estimation, interval, problem 25 102 170 185 199
Euclidean geometry 138
Exchangeability 138 294
Exchangeability between seasons 297
Exchangeability within seasons 300
Expected utility, maximization of 137
Experiments, design of 102
experts 9
extra-sensory perception (ESP) 29
Extreme bounds 253
Feasible ellipsoid 236
Fiducial probabilities 5
Finitely additive priors 110
Foundations of probability 4
Frequencies, relative 5
Frequency, long-run 138
Frequency, measures 85 139 141
Frequented Bayes risk 80
Frequentist 93 126 128
Frequentist risk 86 97
Function, concave 224
Function, convex 225
Function, distance 168 170 172
Global sensitivity 94
Groups, regression in m 255
Helly — Bray theorem 180 189
Hierarchical extreme bounds 256
Hierarchical load curve models 261
Hierarchical model 137
Hierarchical priors 100 140
Hierarchical regression models 246
Hierarchical sensitivity analysis 247
Hyperparameter 246 263 268
Hypotheses, testing 3
Hypothesis, alternative 37
Hypothesis, catchall 10
Hypothesis, composite 151
Hypothesis, null 36
Hypothesis, null testing 34
Hypothesis, simple 153
Hypothesis, test 26
Hypothesis, testing a 'fuzzy' point null hypothesis 95
Ignoring data 103
Indifference curves 34
Inference 2 137
Inference, conditional 70
Inference, probabilities 7
Information contract curve 234 265 282 303
Interocular traumatic test 30
interval 25
Interval, credible 25
Interval, estimation 3 25
Intuition 9
Inversion lemmas 245
Joint distribution 24
judgment 9
Kolmogorov 126
Least-squares 138
Least-squares, restricted 238
Levels, confidence 5
Likelihood 57 137
Likelihood, critical ratios 33
Likelihood, function 107
Likelihood, principle 37 70
Likelihood, ratios 32
Linear estimators 94 98
Local sensitivity 94
Log-odds 138
Long-run, frequency 138
Long-run, performance frequentist 132
Loss, bounded continuous 154
Loss, squared error 153 170 223
Lower variance bound 241
| Marginal density 95
Marginal distribution 24 143
Markov chains 59
Matrix weighted average 234 264 281
Maximization of expected utility 137
Maximum entropy and reference priors 99
Mean 137
Measurability 109
Measurement, stable 92 96
Mechanics, Newtonian 138
Metaprior 81 101 143
Methodologically Bayesian 129
Mill, J.S. 127
minimax 87 127 128 137
Mixed regression 239
Modal estimate 259
Model robustness 85 107
Model, public 9
Multivariate regression systems 231
Newtonian mechanics 138
Non-Bayesian 130
Noninformative priors 73 98
Nonparametric statistics 24
normal 21 137
Normal density 46
Null hypothesis 36
Null hypothesis, testing 34
Objectivity 106
Observations 20
Odds 31
Opinion 2
Paradigms, betting 130
PARAMETER 8 24
Partition 10
Performance frequentist, long run 132
Personal probability 3
Personalistic 138
Point estimate 25
Population 9
Posterior 137
Posterior, robustness 78 92 101 129 137 141
PRECISION 22
Prediction problem 170 185 199
Preference, quasitransitive 71
Principle of stable estimation 10
Prior 137
Prior, approximate 72
Prior, distributions, uniform 11
Prior, finitely additive 110
Prior, hierarchical 100 140
Prior, noninformative 73 98
Prior, probability 8 137
Probabilities, fiducial 5
Probabilities, upper and lower 93 111
Probability theory 4
Procedure, Bayesian 137
Procedure, decision 137
Procedure, robustness 79 95
Procedure, sampling theory 137
Process, Bernoulli 21
Public model 9
Quality control 138
Quasitransitive preference 71
Random sampling 9
Random variable 8
Randomization 83
Rationality, type II 103
Ratios, critical likelihood 25
Reference priors 99
Regression in m groups 255
Regression, mixed 239
Regression, models, hierarchical 246
Regression, systems, multivariate 231
Relative frequencies 5
Restricted least squares 238
Restricted risk, Bayes 89 97
Revision of such opinion 2
Ridge curve 235
Risk functions 128
Risk, Bayes 95
Risk, Bayes, restricted 89 97
Robust  -trimmed mean and variance 128
Robustness 137
Robustness, model 85 107
Robustness, posterior 78 92 101 129 137 141
Robustness, procedure 79 95
Sampling plan 138
Sampling random 9
Sampling theory procedures 137
Seasonal distributed lag 292
Seasonal smoothness model 295 303
Sensitivity, analysis, hierarchical 246
Sensitivity, theory 93
Sequential analysis 93 102
Significance levels 5
Simple dichotomy 32
Simple hypothesis 153
Smoothness model, seasonal 295 303
Snedecor’s F 49
Squared error loss 153 170 223
Stabilizing decision 148 149 150 168 169 171 177 178 181 182 204
Stable measurement 92 96
Stable strongly 146 148 149 150 168 169 171 177 178 181 182 187 190 193 194 195 197 198 199 202 206 209 213 216 217 218 221 222 226
Stable weakly 148 149 150 168 169 171 177 178 181 182 187 190 199 203 209
Standard deviation 16 17
Statistic, ancillary 59
Statistic, classical 3
Statistic, nonparametric 24
Statistic, sufficient 57
Statistical decision theory 3
Statistical inference 4
Stein effect 88 131
Stochastic processes 59
Stopping rules 58
Strongly stable 146 148 149 150 168 169 171 177 178 181 182 187 190 193 194 195 197 198 199 202 206 209 213 216 217 218 221 222 226
Student’s t 24 138
Sufficient statistic 57
Symmetric function 224
Symmetrically restricted bounds 257
Test, interocular traumatic 30
Test, two-tailed classical 45
Testing 102
Testing a 'fuzzy' point null hypothesis 95
Testing hypotheses 3
Theorem, Bayes’ 3 7
Theory, sensitivity 93
Trimmed mean and variance 128
Two-tailed classical test 45
Two-tiered prior distributions 132
Type II rationality 103
Unbiasedness 59
Uncertainty 5
Uniform prior distributions 11
Uniformly bounded 186 187 190 194 197 200 202 203 206 209 216 217 218 219 220 221
Uniformly convergent 168 174 177 181
Uniformly in D, continuous in 154 169 177 186 187
Unstable 148 149 150 168 169 171 177 178 181 182 196 202 204 209 210 213 216 217 219 220 222
Updating 75 140
Upper and lower probabilities 93 111
Upper variance bound 243
Utilitarianism 127
Utility 3 137
Vagueness 18
Variable, random 8
Variance 137
Variance, analysis of 50
Weakly stable 148 149 150 168 169 171 177 178 181 182 187 190 199 203 209
Weber fraction 42
Weber’s law 15
Weighted average, matrix 264 281
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