Results 11 to 20 of about 43 (41)

2000 Mathematics Subject Classification: Primary 62C99, sec-ondary 62C10, 62C20, 62J05

, 2016
The paper deals with recovering an unknown vector β ∈ R^p based on the observations Y = Xβ + ∈ξ and Z = X + σζ, where X is an unknown n×p-matrix with n ≥ p, ξ ∈ R^p is a standard white Gaussian noise, ζ is a n × p-matrix with i.i.d. standard Gaussian entries, and ∈, σ ∈ R^+ are known noise levels. It is assumed that X has a large condition number and p
Golubev, Yu., Zimolo, Th.
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Personalized decision making – A conceptual introduction

Journal of Causal Inference, 2023
Personalized decision making targets the behavior of a specific individual, while population-based decision making concerns a subpopulation resembling that individual.
Mueller Scott, Pearl Judea
doaj   +1 more source

Decision-theoretic foundations for statistical causality

Journal of Causal Inference, 2021
We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic (DT) statistical causality, which is a straightforward way of representing and addressing causal questions.
Dawid Philip
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Decision-theoretic foundations for statistical causality: Response to Pearl

Journal of Causal Inference, 2022
I thank Judea Pearl for his discussion of my paper and respond to the points he raises. In particular, his attachment to unaugmented directed acyclic graphs has led to a misapprehension of my own proposals. I also discuss the possibilities for developing
Dawid Philip
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Decision-theoretic foundations for statistical causality: Response to Shpitser

Journal of Causal Inference, 2022
I thank Ilya Shpitser for his comments on my article, and discuss the use of models with restricted interventions.
Dawid Philip
doaj   +1 more source

Causation and decision: On Dawid’s “Decision theoretic foundation of statistical causality”

Journal of Causal Inference, 2022
In a recent issue of this journal, Philip Dawid (2021) proposes a framework for causal inference that is based on statistical decision theory and that is, in many aspects, compatible with the familiar framework of causal graphs (e.g., Directed Acyclic ...
Pearl Judea
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MR1340500 (96h:90007) Morrell, Darryl; Driver, Eric Bayesian network implementation of Levi's epistemic utility decision theory. Internat. J. Approx. Reason. 13 (1995), no. 2, 127â 149. (Reviewer: Nicola Mattoscio), 90A05 (62C99)

, 1995
MATTOSCIO, Nicola
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On the Ferrers property of valued interval orders

, 2011
Total interval order, Partial interval order, Ferrers property, Valued relation, Completeness, 62C99, 91B08, 04A72,
Susana Díaz, Susana Montes, De Baets, Bernard, Montes Rodríguez, Susana, Bernard Baets, Montes, Susana, Baets, Bernard de, Diáz, Susana, Díaz Vázquez, Susana   +8 more
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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

Novel time series methods in economic forecasting: SutteARIMA evidence from Indonesian Consumer Price Index and currency exchange rates

Cogent Economics & Finance
Economic forecasting demands precision. Yet traditional models often stumble when confronted with real-world complexity – the messy interplay of linear trends, non-linear disruptions and seasonal fluctuations that characterize financial time series. This
Ansari Saleh Ahmar, Eva Boj del Val
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