We investigate the average characteristic polynomial E [∏N i=1(z−xi) ] where the xi’s are real random variables drawn from a Biorthogonal Ensemble, i.e. a determinantal point process associated with a bounded finite-rank projection operator. For a subclass of Biorthogonal Ensembles, which contains Orthogonal Polynomial Ensembles and (mixed-type) Multiple Orthogonal Polynomial Ensembles, we prov...

This paper study the recent seismicity in Earthquake hazard zones in India. A large historical earthquake event catalog to cover the period of 1900-2018, the parameters date, time, latitude, longitude, depth and magnitude has been used to calculating frequency-magnitude distribution (b-value) of seismic hazard zones in India. To convert different magnitude scales into a single moment magnitude ...

Inference for statistics of a stationary time series often involve nuisance parameters and sampling distributions that are difficult to estimate. In this paper, we propose the method of orthogonal samples, which can be used to address some of these issues. For a broad class of statistics, an orthogonal sample is constructed through a slight modification of the original statistic, such that it s...

We derive efficient recursive formulas giving the exact distribution of the largest eigenvalue for finite dimensional real Wishart matrices and for the Gaussian Orthogonal Ensemble (GOE). In comparing the exact distribution with the limiting distribution of large random matrices, we also found that the Tracy-Widom law can be approximated by a properly scaled and shifted gamma distribution, with...

This paper presents an extended polynomial dimensional decomposition method for solving stochastic problems subject to independent random input following an arbitrary probability distribution. The method involves Fourier-polynomial expansions of component functions by orthogonal polynomial bases, the Stieltjes procedure for generating the recursion coefficients of orthogonal polynomials and the...

In this paper, we show that the projection of a regular orthogonal array of strength t onto more than t factors consists of replicates of either a fractional factorial or a full factorial design of strength t, depending on the number of factors retained in the projection.

In this paper we show additional properties of the limit of the sequence produced by the subspace correction algorithm proposed by Fornasier and Schönlieb [24] for L2/TV -minimization problems. Inspired by the work of Vonesch and Unser [34], we adapt and specify this algorithm to the case of an orthogonal wavelet space decomposition and for deblurring problems.