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Calibrating predictive distributions [PDF]

Journal of Statistical Computation and Simulation, 2012
This paper concerns prediction from the frequentist point of view. The aim is to define a well-calibrated predictive distribution giving prediction intervals, and in particular prediction limits, with coverage probability equal or close to the target nominal value.
FONSECA, Giovanni, GIUMMOLE' F, VIDONI, Paolo   +2 more
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Prediction limits for an exponential distribution: a Bayes predictive distribution approach

IEEE Transactions on Reliability, 1989
A life testing experiment that has a one-parameter exponential distribution with constant failure rate is considered. Using the gamma prior, the authors derive the posterior distribution for that failure rate and hence the predictive distribution of future observations. Available data are from type II censored sampling.
Upadhyay, S. K., Pandey, M.
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Predictive search distributions

Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006
Estimation of Distribution Algorithms (EDAs) are a popular approach to learn a probability distribution over the "good" solutions to a combinatorial optimization problem. Here we consider the case where there is a collection of such optimization problems with learned distributions, and where each problem can be characterized by some vector of features.
Edwin V. Bonilla, Christopher K. I. Williams, Felix V. Agakov, John Cavazos, John Thomson, Michael F. P. O'Boyle   +5 more
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Asymptotics of Predictive Distributions

2016
Let \((X_n)\) be a sequence of random variables, adapted to a filtration \((\mathcal {G}_n)\), and let \(\mu _n=(1/n)\,\sum _{i=1}^n\delta _{X_i}\) and \(a_n(\cdot )=P(X_{n+1}\in \cdot \mid \mathcal {G}_n)\) be the empirical and the predictive measures. We focus on \(||\mu _n-a_n||=\sup _{B\in \mathcal {D}}\,|\mu _n(B)-a_n(B)|\), where \(\mathcal {D}\)
Patrizia Berti, Luca Pratelli, Pietro Rigo   +2 more
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Distributed Bounded Predictability

2013 32nd International Conference of the Chilean Computer Science Society (SCCC), 2013
Complex systems often exhibit unexpected faults that are difficult to handle. A system that is predictable can anticipate faults and act accordingly. In particular, bounded predictability offers information that can be exploited by the system to adopt the best contingency plan. Such information is offered in form of a lower and upper bound.
Laura Brandan Briones, Agnes Madalinski
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Optimal estimates of predictive distributions

Biometrika, 1980
Approximations to Bayesian predictive density functions p(y I x) are sought with the use of the Kullback & Leibler (1951) directed measure of divergence. The approximations are constrained to lie in the same family of distributions as the underlying model p(y 0). The optimal approximations are found to coincide for the case of vague knowledge with some
Amaral, Maria Antonia, Dunsmore, Ian R.
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Cooperative distributed model predictive control

Systems & Control Letters, 2010
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STEWART BT, VENKAT AN, RAWLINGS JB, WRIGHT SJ, PANNOCCHIA, GABRIELE   +4 more
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Frequentist prediction intervals and predictive distributions

Biometrika, 2005
SUMMARY We consider parametric frameworks for the prediction of future values of a random variable Y, based on previously observed data X. Simple pivotal methods for obtaining calibrated prediction intervals are presented and illustrated. Frequentist predictive distri butions are defined as confidence distributions, and their utility is demonstrated. A
J. F. Lawless, Marc Fredette
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Distributed model predictive control for energy distribution

2013 European Control Conference (ECC), 2013
This work presents a distributed model predictive control scheme for energy distribution. The energy is supposed to be supplied by a renewable power system whose energy production is limited and demanded by several consumers. Therefore, in some cases the produced energy cannot fulfill the energy requirements of the consumers.
H.F. Scherer, M. Pasamontes, J.D. Alvarez, J.L. Guzman, E. Camponogara, J.E. Normey-Rico   +5 more
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Prediction Intervals for IFR Distributions

IEEE Transactions on Reliability, 1980
Several prediction intervals for the class of increasing failure rate distributions are obtained. They extend some known results on 1-or 2-parameter exponential distributions. The use of these results requires no new tables.
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