Search results for "Decision theory"
showing 5 items of 25 documents
How does information technology– based service degradation influence consumers’ use of services? An information technology–based service degradation …
2019
Information technology is crucial for modern services. Service delivery may include a complex mix of information technology and telecommunication providers, global networks and customers’ information technology devices. This research focuses on service failures that are caused by information technology problems, which we conceptualize as information technology-based service degradation (ITSD). When information technology-based service degradation occurs in a modern service, the information technology problem may originate from the service provider, another partner or any information technology equipment involved. But the customer may not be able to pinpoint the source of the problem immedi…
The Multivariate Individual Selection of Diagnostic Tests and the Reserved Diagnostic Statement: An Optimum Combination of Two New Methods for the Co…
1984
A combination of two new methods for the diagnostic procedure in computer-aided differential diagnosis is presented. It is constructed on the basis of new results of our own in the field of mathematical decision theory and is demonstrated by the differential diagnosis of congenital heart diseases by means of ECG features.
Asymptotic optimality of myopic information-based strategies for Bayesian adaptive estimation
2016
This paper presents a general asymptotic theory of sequential Bayesian estimation giving results for the strongest, almost sure convergence. We show that under certain smoothness conditions on the probability model, the greedy information gain maximization algorithm for adaptive Bayesian estimation is asymptotically optimal in the sense that the determinant of the posterior covariance in a certain neighborhood of the true parameter value is asymptotically minimal. Using this result, we also obtain an asymptotic expression for the posterior entropy based on a novel definition of almost sure convergence on "most trials" (meaning that the convergence holds on a fraction of trials that converge…
Statistical inference and Monte Carlo algorithms
1996
This review article looks at a small part of the picture of the interrelationship between statistical theory and computational algorithms, especially the Gibbs sampler and the Accept-Reject algorithm. We pay particular attention to how the methodologies affect and complement each other.
Eleccion de variables en regresion lineal un problema de decision
1986
A general structure for the problem of selection of variables in regression is proposed using the decision theory framework. In particular, some results for the choice of the best linear normal homocedastic model are obtained when the main purpose is either to specify the predictive distribution over the response variable or to obtain a point estimate of it. A comparison of our results with the most widespread classical ones is presented