Results 241 to 250 of about 384,025 (280)

Information and Conditional Inference

Journal of the American Statistical Association, 1995
Abstract Consider non-Bayesian inference about a parameter of interest β in the presence of a nuisance parameter λ based on a statistic S = (T, A). If the conditional distribution of T given A does not depend on λ and if A contains no information about β in the presence of λ, then A is said to be ancillary for θ in the presence of λ, and inference ...
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Inference and Conditional Knowledge

Dialogue, 1981
It is often said that knowledge is justified true belief. But when is a belief justified? Again, it is often said, that belief is justified when it is entailed by something I know. As a definition of knowledge, this account is circular and generates a regress. So much then for justified true belief. Still, knowledge must certainly be true and believed,
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Plausible inference for default conditionals

2005
This paper presents a monotonic core logic for default conditionals and \u000Ainvestigates possible nonmonotonic extensions. First, we introduce a possible \u000Aworlds semantics characterizing HRC0, a strong logic for non‐nested normal \u000Aimplication.
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How Robust is Conditional Inference?

2001
The aim of this contribution is to investigate the stability of approximate conditional procedures used to eliminate nuisance parameters in regression-scale models.
BRAZZALE, ALESSANDRA ROSALBA, VENTURA, LAURA   +1 more
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Conditional Inference is not Inefficient

1977
A paper of Welch (1939) is often referred to as demonstrating the inefficiency of conditional confidence intervals. It is the object of this note to show that such a notion arises from a misunderstanding.
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Disabling conditional inferences: An EEG study

Neuropsychologia, 2014
Although the Modus Ponens inference is one of the most basic logical rules, decades of conditional reasoning research show that it is often rejected when people consider stored background knowledge about potential disabling conditions. In the present study we used EEG to identify neural markers of this process.
Mathilde, Bonnefond, Mariia, Kaliuzhna, Jean-Baptiste, Van der Henst, Wim, De Neys   +3 more
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Computer-intensive conditional inference

2010
Conditional inference is a fundamental part of statistical theory. However, exact conditional inference is often awkward, leading to the desire for methods which offer accurate approximations. Such a methodology is provided by small-sample likelihood asymptotics.
G. Alastair Young, Thomas J. DiCiccio
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Conditional Inference

2022
E. L. Lehmann, Joseph P. Romano
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Conditional Natural Language Inference

Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Youngwoo Kim, Razieh Rahimi, James Allan
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Conditional Inference

2000
N. Balakrishnan, Rita Aggarwala
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