stochastically


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sto·chas·tic

(stō-kăs′tĭk)
adj.
1. Of, relating to, or characterized by conjecture; conjectural.
2. Statistics Involving or containing a random variable or process: stochastic calculus; a stochastic simulation.

[Greek stokhastikos, from stokhastēs, diviner, from stokhazesthai, to guess at, from stokhos, aim, goal; see stegh- in Indo-European roots.]

sto·chas′ti·cal·ly adv.
American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Adv. 1. stochastically - by stochastic means; "we estimated the answer stochastically"
Based on WordNet 3.0, Farlex clipart collection. © 2003-2012 Princeton University, Farlex Inc.
References in periodicals archive ?
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.
At the same time the resistance of such load as a metal granular layer can stochastically increase several times during discharge.
Stochastically 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.
(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.
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