Billingsley — Statistical inference for Markov processes,
Statistical inference for renewal processes
... These issues are clearly explained in Hoffmann and Olivier (2016) who consider a related model: age dependent branching processes. Our framework can be formalized as a degenerate age depen- dent branching process: ...
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Statistical inference for spatial and spatio temporal processes
... stationary processes on Zd\ either this is for a unilateral spatio- tem poral process or a spatial process on Zd, the same idea has been used ...two processes share together the general Yule-Walker ...two ...
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Statistical Inference for Discrete-Valued Stochastic Processes
... Finally, the asymptotic behavior of the test statistic is derived, allowing us to evaluate the significance of deviations of the test statistic. Even though they share one basic approach, the mathematical tools involved ...
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Statistical inference for periodic and partially observable poisson processes
... 5.2 Parameter Estimation with Signal and Background Model 75 5.2 Parameter Estimation with Signal and Background Model Some of the practical problems involving counting processes can be reduced to the case of ...
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Statistical Inference for Networks of High-Dimensional Point Processes
... point processes do not provide measures of uncertainty, which are critical in scientific ...on statistical inference in high dimensions ...developing inference procedures for multivariate ...
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Statistical inference for negative binomial processes with applications to market research
... Chapter 1 4 C hapter 5 applies the results of Chapters 3 and 4 to m arket research d a ta kindly provided by ACNielsen BASES. T he d ata comprises of raw transaction d a ta obtained from the scanning of individual item s ...
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Exact Statistical Inference for Some Parametric Nonhomogeneous Poisson Processes
... 1 Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway. 2 SINTEF ICT, Trondheim, Norway. Abstract. Nonhomogeneous Poisson processes (NHPPs) are often used to model ...
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Statistical inference for Vasicek-type model driven by Hermite processes
... Hermite processes Z q,H of order q > 2 form a class of genuine non-Gaussian generalizations of the celebrated fractional Brownian motion (fBm), this latter corresponding to the case q = ...of processes, ...
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On the problems of sequential statistical inference for Wiener processes with delayed observations
... Wiener processes with constant drift rates by Shiryaev ( 1978 , ...Poisson processes with unknown intensities was introduced and solved by Davis ( 1976 ) given certain restrictions on the model ...Poisson ...
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Unbiased Bayesian inference for population Markov jump processes via random truncations
... Bayesian inference for such systems remains challenging, as these are contin- uous time, discrete state systems with potentially infi- nite ...population Markov Jump ...
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Statistical inference of 2-type critical Galton–Watson processes with immigration
... branching processes with immigration has a long history, see the survey paper of Winnicki ...Galton–Watson processes with immigration for which statistical inference is available: the unstable ...
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Application of order restricted statistical inference and hidden Markov modeling to problems in biology and genomics
... CHAPTER 2. Testing a Union-of-Cones Null Hypothesis for the Identification of Heterosis Abstract High-parent or low-parent heterosis is a genetic phenomenon that occurs when the mean trait value of offspring is more ...
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A Simple and Efficient Statistical Model Checking Algorithm to Evaluate Markov Decision Processes
... falsifies the property, the algorithm returns false and the counter-example σ d . If no such scheduler is found, the algorithm returns probablytrue, meaning that the property is probably satisfied, with a confidence that ...
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Statistical inference for first order random coefficient integer valued autoregressive processes
... Abstract In this paper, we apply the least-squares method to estimate the unknown parameters in first-order random coefficient integer-valued autoregressive (RCINAR(1)) processes. The least-squares estimator is ...
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Inference and rare event simulation for stopped Markov processes via reverse time sequential Monte Carlo
... 5 Discussion We have presented a general framework for designing SMC proposal distributions which proceed backwards in time. Time-reversal makes it straightforward to ensure realisations of the process hit desired ...
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Scalable Bayesian inference for coupled hidden Markov and semi-Markov models
... Bayesian inference for coupled hidden Markov models frequently relies on data augmentation techniques for imputation of the hidden state ...using Markov chain Monte Carlo (MCMC) ...hidden ...
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Elliptic Combinatorics and Markov Processes
... Schur processes of [OR03] and Macdonald processes of [Vul09], ...such processes correspond to the previously mentioned elliptic measures on tilings of a ...elliptic processes should be of use ...
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Sufficient Markov Decision Processes.
... Sufficient Markov Decision ...health. Markov decision processes are the primary mathematical model for sequential decision problems with a large or indefinite time horizon; existing methods for ...
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Elliptic Combinatorics and Markov Processes
... Schur processes of [OR03] and Macdonald processes of [Vul09], ...such processes correspond to the previously mentioned elliptic measures on tilings of a ...elliptic processes should be of use ...
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Robust Markov Decision Processes
... Although transition sampling has theoretical appeal, it is often prohibitively costly or even infeasible in practice. To obtain independent samples for each state-action pair, one needs to repeatedly direct the MDP into ...
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