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This paper explores a Gaussian process emulator based approach for rapid Bayesian inference of contaminant source location and characteristics in an indoor environment. In the pre-event detection stag...
The stochastic block model (SBM) is a mixture model used for the clustering of nodes in networks. It has now been employed for more than a decade to analyze very different types of networks in many sc...
Murray Aitkin's recent book, Statistical Inference, presents an approach to statistical hypothesis testing based on comparisons of posterior distributions of likelihoods under competing models. The au...
In this paper we develop a scientific approach to control inter-country conflict. This system makes use of a neural network and a feedback control approach. It was found that by controlling the four c...
We consider a positive stationary generalized Ornstein–Uhlenbeck process Vt = e−tZ t0es− ds + V0 for t  0,and the increments of the integrated generalized Ornstein–Uhlenbeck process...
The integrated square error (ISE) and the mean integrated squark error (MISE) for a class of recursive estimators of the transition density function of a vector-valued nonstationary Markov process ...
Metric entropy of the class of probability distribution functions on [0,1] with a k-monotone density is studied through its connection with the small ball probability of k-times integrated Brownian mo...
In this paper, we consider a continuous-time autoregressive fractionally integrated moving average(CARFIMA) model, which is defined as the stationary solution of a stochastic differential equation dr...
In this paper we prove the Local Asymptotic Mixed Normality (LAMN) property for the statistical model given by the observation of local means of a diffusion process X. Our data are given by R 10 Xs...
We prove uniform convergence results for the integrated periodogram of a weakly dependent time series,namely a law of large numbers and a central limit theorem. These results are applied toWhittle’s p...

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