Although cell fate specification is tightly controlled to yield highly reproducible results and avoid extreme variation, developmental programs often incorporate stochastic mechanisms to diversify cell types. Stochastic specification phenomena are observed in a wide range of species and an assorted set of developmental contexts. In bacteria, stochastic mechanisms are utilized to generate transi...

We study the effect of introducing stochastic volatility in the first passage structural approach to default risk. We analyze the impact of volatility time scales on the yield spread curve. In particular we show that the presence of a short time scale in the volatility raises the yield spreads at short maturities. We argue that combining first passage default modeling with multiscale stochastic...

Cover’s celebrated theorem states that the long run yield of a properly chosen “universal” portfolio is as good as the long run yield of the best retrospectively chosen constant rebalanced portfolio. The “universality” pertains to the fact that this result is model-free, i.e., not dependent on an underlying stochastic process. We extend Cover’s theorem to the setting of stochastic portfolio the...

Spatio-temporal analyses of yield variability are required to delineate areas of stable yield patterns for application of precision farming techniques. Spatial structure and temporal stability patterns were studied using 19951997 yield data for a 25-ha field located near Story City, Iowa. Corn was grown during 1995-1996, and soybean in 1997. The yield data were collected on nine east-west trans...

Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...

In this paper, we develop and apply Bayesian inference for an extended NelsonSiegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov chain Monte Carlo (MCMC) algorithm to efficiently estimate the SVNS model using simulation-based inference...

SYNOPSIS This paper reports the first predictions of the yield stress of suspensions of non-Brownian magnetic fibers in the presence of uniform magnetic fields. The quasi-static regime of the shear deformation (before the flow onset) of the suspension is studied. Four different structures of the magnetic fiber suspensions are considered – column, zigzag, 3D stochastic and near-planar stochastic...