Results 21 to 30 of about 132 (45)

Potential outcomes and decision-theoretic foundations for statistical causality: Response to Richardson and Robins

Journal of Causal Inference
I thank Thomas Richardson and James Robins for their discussion of my article, and discuss the similarities and differences between their approach to causal modelling, based on single world intervention graphs, and my own decision-theoretic approach.
Dawid Philip
doaj   +1 more source

Riemannian Holonomy Groups of Statistical Manifolds [PDF]

, 2014
Normal distribution manifolds play essential roles in the theory of information geometry, so do holonomy groups in classification of Riemannian manifolds.
Jiu, Lin, Li, Didong, Sun, Huafei, Tao, Chen   +3 more
core  

Probability theory and its models

, 2008
This paper argues for the status of formal probability theory as a mathematical, rather than a scientific, theory. David Freedman and Philip Stark's concept of model based probabilities is examined and is used as a bridge between the formal theory and ...
Humphreys, Paul
core   +1 more source

Prior distributions for objective Bayesian analysis [PDF]

, 2018
We provide a review of prior distributions for objective Bayesian analysis. We start by examining some foundational issues and then organize our exposition into priors for: i) estimation or prediction; ii) model selection; iii) highdimensional models ...
Consonni, Guido, Fouskakis, Dimitris, Liseo, Brunero, Ntzoufras, Ioannis   +3 more
core   +1 more source

From urn models to box models: Making Neyman's (1923) insights accessible

Journal of Causal Inference
Neyman’s 1923 paper introduced the potential outcomes framework and the foundations of randomization-based inference. We discuss the influence of Neyman’s paper on four introductory to intermediate-level textbooks by Berkeley faculty members (Scheffé ...
Lin Winston, Dudoit Sandrine, Nolan Deborah, Speed Terence P.   +3 more
doaj   +1 more source

On asymptotically optimal tests under loss of identifiability in semiparametric models [PDF]

, 2009
We consider tests of hypotheses when the parameters are not identifiable under the null in semiparametric models, where regularity conditions for profile likelihood theory fail.
Fine, Jason P., Kosorok, Michael R., Song, Rui   +2 more
core   +3 more sources

A nonmanipulable test

, 2009
A test is said to control for type I error if it is unlikely to reject the data-generating process. However, if it is possible to produce stochastic processes at random such that, for all possible future realizations of the data, the selected process is ...
Olszewski, Wojciech, Sandroni, Alvaro
core   +2 more sources

Spillover detection for donor selection in synthetic control models

Journal of Causal Inference
Synthetic control (SC) models are widely used to estimate causal effects in settings with observational time-series data. To identify the causal effect on a target unit, SC requires the existence of additional units that are not impacted by the ...
O’Riordan Michael, Gilligan-Lee Ciarán M.   +1 more
doaj   +1 more source

Decision making, symmetry and structure: Justifying causal interventions

Journal of Causal Inference
We can use structural causal models (SCMs) to help us evaluate the consequences of actions given data. SCMs identify actions with structural interventions. A careful decision maker may wonder whether this identification is justified.
Johnston David O., Ong Cheng Soon, Williamson Robert C.   +2 more
doaj   +1 more source

Fiducial theory and optimal inference

, 2013
It is shown that the fiducial distribution in a group model, or more generally a quasigroup model, determines the optimal equivariant frequentist inference procedures.
Lindqvist, Bo Henry, Taraldsen, Gunnar
core   +1 more source