|
|
|
|
LEADER |
01000caa a22002652 4500 |
001 |
JST052571653 |
003 |
DE-627 |
005 |
20240621205452.0 |
007 |
cr uuu---uuuuu |
008 |
150324s1991 xx |||||o 00| ||eng c |
035 |
|
|
|a (DE-627)JST052571653
|
035 |
|
|
|a (JST)2345729
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Dawid, A. P.
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Fisherian Inference in Likelihood and Prequential Frames of Reference
|
264 |
|
1 |
|c 1991
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a Computermedien
|b c
|2 rdamedia
|
338 |
|
|
|a Online-Ressource
|b cr
|2 rdacarrier
|
520 |
|
|
|a In celebration of the centenary of the birth of Sir Ronald Fisher, this paper explores Fisher's conception of statistical inference, with special attention to the importance he placed on choosing an appropriate frame of reference to define the inferential model. In particular, we investigate inferential models which respect the likelihood principle or the prequential principle, and argue that these will typically have an asymptotic sampling theory justification.
|
540 |
|
|
|a Copyright 1991 Royal Statistical Society
|
650 |
|
4 |
|a Asymptotic Estimation Theory
|
650 |
|
4 |
|a Bayesian Inference
|
650 |
|
4 |
|a Inferential Model
|
650 |
|
4 |
|a Prediction Error
|
650 |
|
4 |
|a Prequential Principle
|
650 |
|
4 |
|a Production Model
|
650 |
|
4 |
|a Production Principle
|
650 |
|
4 |
|a R. A. Fisher
|
650 |
|
4 |
|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Thought processes
|x Reasoning
|x Inference
|
650 |
|
4 |
|a Physical sciences
|x Physics
|x Mathematical physics
|x Observational frames of reference
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
|x Maximum likelihood estimators
|
650 |
|
4 |
|a Applied sciences
|x Research methods
|x Modeling
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical distributions
|x Normal distribution curve
|x Sampling distributions
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical results
|x Statistical properties
|x Statistical discrepancies
|
650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Probability theory
|x Probabilities
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Analytics
|x Predictive analytics
|x Analytical forecasting
|x Forecasting models
|
650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical inferences
|
655 |
|
4 |
|a research-article
|
773 |
0 |
8 |
|i Enthalten in
|t Journal of the Royal Statistical Society. Series B (Methodological)
|d Royal Statistical Society, 1948
|g 53(1991), 1, Seite 79-109
|w (DE-627)30219746X
|w (DE-600)1490719-7
|x 00359246
|7 nnns
|
773 |
1 |
8 |
|g volume:53
|g year:1991
|g number:1
|g pages:79-109
|
856 |
4 |
0 |
|u https://www.jstor.org/stable/2345729
|3 Volltext
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_JST
|
912 |
|
|
|a GBV_ILN_120
|
912 |
|
|
|a GBV_ILN_374
|
912 |
|
|
|a GBV_ILN_380
|
951 |
|
|
|a AR
|
952 |
|
|
|d 53
|j 1991
|e 1
|h 79-109
|