The expectation maximisation algorithm (EM) was introduced by Dempster, Laird and Rubin in 1977 [DLR77]. The basic of expextation maximisation is maximum likelihood estimation (MLE). In modern sensor data fusion expectation maximisation becomes a substantial part in several applications, e.g. multi target tracking with probabilistic multi hypothesis tracking (PMHT), target extraction within pro...

various statistical methods have been proposed in terms of predicting the outcomes of facing special factors. in the classical approaches,  making the probability distribution or known probability density functions is ordinarily necessary to predict the desired outcome. however, most of the times enough information about the probability distribution of studied variables is not available to the ...

Instantaneous volatility of logarithmic return in the lognormal fractional SABR model is driven by exponentiation a correlated Brownian motion. Due to mixed nature driving and motions, probability density for such less studied literature. We show this paper bridge representation joint Fourier space. Evaluating along properly chosen deterministic path yields small time asymptotic expansion leadi...