Finally, the researchers investigated as well how it might be modeled in a randomized way ('stochastically
'), which would better capture what happens in real cells.
The inherent stochastic behavior of the magnet was used to switch the magnetization states stochastically
based on the proposed algorithm for learning different object representations.
This approach is generally used to test whether one series stochastically
dominates the other one at any specific stochastic order.
A desired and natural consequence of the MCPT definition is that stochastic dominance in the traditional sense is violated; that is, if the terminal value of investment A stochastically
dominates (6) investment B, investment A does not necessarily have a higher MCPT utility than investment B.
In all of the above examples any attempts to build a stochastic model of observations quickly lead to stochastically
dependent sequences of random variables.
At the same time the resistance of such load as a metal granular layer can stochastically
increase several times during discharge.
sampling the rainfall duration is arguably more theoretically sound than critical duration concept.
In the case where a mixed strategy equilibrium occurs both before and after the merger, moreover, the support of the price distributions shifts rightward after the merger and the postmerger price distribution of each firm stochastically
dominates its premerger counterpart.
The holes are arranged stochastically
, out of line with each other, thereby eliminating the risk of undesired patterns becoming visible in printed results.
* NRAP Seal Reduced-Order model (NSealR) estimates migration of brine and supercritical C02 through an imperfect (fractured or perforated) seal barrier above the injection horizon using stochastically
defined parameters and Monte Carlo analyses, useful for estimating containment effectiveness.
(Other winter months yielded similar results.) Figure 4.1 shows histograms of monthly ERSST.V5 Nino3 and Nino4 indices, compared with two different probability distribution functions (PDFs) determined not by fitting the histogram, but by fitting two different Markov processes to each index time series: an AR1 process (or red noise; e.g., Frankignoul and Hasselmann 1977) with a memory time scale on the order of several months, yielding a Gaussian (normal) distribution; and a "stochastically
generated skewed" process (SGS; Sardeshmukh et al.
That is, when the local scale factor is evaluated at a given spacetime point, its dynamics is dictated (sourced) by the stochastically
varying vacuum fluctuations at that point.