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In the present paper, a fuzzy logic based method is combined with wavelet decomposition to develop a step-by-step dynamic hybrid model for the estimation of financial time series. Empirical tests on ...
In this paper we consider estimation of sparse covariance matrices and propose a thresholding procedure which is adaptive to the variability of individual entries. The estimators are fully data driven...
A constrained L1 minimization method is proposed for estimating a sparse inverse covariance matrix based on a sample of $n$ iid $p$-variate random variables. The resulting estimator is shown to enjoy ...
We propose a non-parametric statistical procedure for detecting multiple change-points in multidimensional signals. The method is based on a test statistic that generalizes the well-known Kruskal-Wall...
We study the smoothed log-concave maximum likelihood estimator of a probability distribution on $\mathbb{R}^d$. This is a fully automatic nonparametric density estimator, obtained as a canonical smoot...
Data produced by two different sources is classified using variable length Markov chains. In many realistic situations it is conceiveable that the probabilistic context trees corresponding to the two ...
The problem of decentralized parameter estimation is considered for diffusion-type processes whose drift coefficients are linear with respect to the unknown parameter. This problem is motivated by app...
We study maximum likelihood estimation in Gaussian graphical models from a geometric point of view. An algebraic elimination criterion allows us to find exact lower bounds on the number of observation...
We consider the problem of learning the structure of graphical models by estimating the inverse covariance matrix with sparsity regularization. We develop a new method based on split Bregman to solve ...
Motivated by fluorescence lifetime measurements this paper considers the problem of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-u...
In linear regression problems with related predictors, it is desir-able to do variable selection and estimation by maintaining the hi-erarchical or structural relationships among predictors. In this p...
The paper considers the problem of robust estimating a periodic function in a continuous time regression model with dependent disturbances given by a general square integrable semimartingale with unk...
A statistical framework is introduced for a broad class of problems involving synchronization or registration of data across a sensor network in the presence of noise. This framework enables an estim...
Consistency, almost sure convergence and central limit theorems are provided for two nonparametric estimators of the local Hurst function of Gaussian multifractional processes. In the case of multifr...

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