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We propose a generalization of the discrete Klein-Gordon models free of the Peierls-Nabarro barrier derived in Spreight [Nonlinearity 12, 1373 (1999)] and Barashenkov et al. [Phys. Rev. E 72, 035602(R...
For a discrete, translationally invariant phi4 model introduced by Barashenkov et al (2005 Phys. Rev. E 72 35602R), we provide the momentum conservation law and demonstrate how the first integral of t...
This paper reconsiders the problem of calculating the expected set of probabilities , given the observed set of items {m_i}, that are distributed among n bins with an (unknown) set of probabiliti...
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...
A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output ...
The Metropolis-Hastings (MH) algorithm is the prototype for a class of Markov chain Monte Carlo methods that propose transitions between states and then accept or reject the proposal. These methods g...
We calculate the marginal probability density of real and complex Wishart correlation matrices. For deep mathematical reasons, no explicit expression could be obtained for the real case so far. We cir...
The group lasso is a penalized regression method, used in regression problems where the covariates are partitioned into groups to promote sparsity at the group level. Existing methods for finding the ...
Efron [Biometrika 58 (1971) 403--417] developed a restricted randomization procedure to promote balance between two treatment groups in a sequential clinical trial. He called this the biased coin des...
We derive exact formulas for the false discovery rate (FDR) and the Power of any step-up and step-down procedures and for the s- th moment of the false discovery proportion (FDP) of any step-up pro...
Exact lower bounds on the exponential moments of min(y,X) and X I {X < y} are provided given the first two moments of a random variable X. These bounds are useful in work on large deviations probabi...
BSA-exact algorithm computing LTS estimate      BSA  exact algorithm  LTS estimate        font style='font-size:12px;'> 2010/3/9
The main result of this paper is a new exact algorithm computing the estimate given by the Least Trimmed Squares (LTS). The algorithm works under very weak assumptions. To prove that, we study the r...
Bayesian belief networks provide estimates of conditional probabilities, called query responses. The precision of these estimates is assessed using posterior distributions. This paper discusses two ...
We derive an exact and efficient Bayesian regression algorithm for piece- wise constant functions of unknown segment number, boundary locations, and lev- els. The derivation works for any noise and ...
Complete exact laws      Strong law of large numbers  weak law of large numbers  complete convergence       font style='font-size:12px;'> 2009/9/22
Consider independent and identically distributed random variables (x,X ,,n, > i ) with xP {X > x ) - a (log x)", where a: > -1 and P{X < -x) = o(P{X > x)). Even though the mean does not exist, we ...

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