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Probabilistic k-nearest neighbour (PKNN) classification has been introduced to improve the performance of original k-nearest neighbour (KNN) classification algorithm by explicitly modelling uncertaint...
In this paper, we observe a fixed number of unknown $2\pi$-periodic functions differing from each other by both phases and amplitude. This semiparametric model appears in literature under the name "s...
An Markov chain Monte Carlo simulation method based on a two stage delayed rejection Metropolis-Hastings algorithm is proposed to estimate a factor multivariate stochastic volatility model. The firs...
The paper deals with asymptotic properties of the adaptive proce- dure proposed in the author paper, 2007, for estimating an unknown nonparametric regression. We prove that this procedure is asympto...
paper considers the efficient estimation of copula-based semi- parametric strictly stationary Markov models. These models are char- acterized by nonparametric invariant (one-dimensional marginal) di...
F.Giroire has recently proposed an algorithm which returns the approximate number of distincts elements in a large sequence of words, under strong constraints coming from the analysis of large data b...

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