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This mapping transforms a high-dimensional random parameter vector, which may represent the stochastic input load as well as any uncertain structural parameters, into a random variable with unknown distribution, which represents the uncertain structural response.
Between two refinancing dates, the financing policy described fixes the debt level to (D_{t+nk}) and the leverage ratio (widetilde{l}_{s}=D_{t+nk}/widetilde{V}^L_s) turns into a random variable.
With multiple probable scenarios, the objective function ( xi = c^{T} x + d^{T} y ) turns into a random variable that takes the value ( xi_{s} = c^{T} x + d_{s}^{T} y_{s} ), with probability ( p_{s} ).
Therefore, we change the maximum growth rate m in the turbidostat model into a random variable m̃, in there (tilde{m}=m+alpha dot{B}(t)), where (dot{B}(t)) is white noise, i.e., (B t)) is a standard Brownian motion defined on a complete probability space ((Omega,mathcal{F},P)) (where (mathcal{F}_{t}=sigma{(S t),x t)); 0leq tleqtau_{e}}) is σ-filed generated by ((S t),x t))), (0leq tleqtau_{e})).
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We model an IDU's time at first incarceration because initiation into injecting, X, as a random variable using piecewise constant annual incarceration rates over 3 injecting-career-length intervals of 0 5, 6 10, and ≥11 years, denoted p1, p2, and p3, respectively.
Summarizing the whole support of a random variable into minimum volume sets of its probability density function is studied in the paper.
Monte-Carlo simulation was applied as a subroutine in the main program to generate a random variable into both groundwater model and slope stability analysis.
A few of them treated the stochastic component, for instance, Li and Yeh (2002) added a random variable into the probability function in ANN-CA model, Wu (2002) combined Monte Carlo approach with probability generalized by statistical method in urban and non-urban simulations.
The distribution of the log-likelihood test statistic (minus two times the log-likelihood ratio) can be approximated taking into account the distribution of a random variable which takes the value 0 with probability 0.5 and takes on a value from a χ2 distribution with 1 degree of freedom with 0.5 probability [ 10].
At every branching step, the "parent" branch divides into N "child" branches (N being a random variable with a defined probability distribution).
To avoid pseudoreplication derived from the lack of independence in values from nestlings within the same brood and sharing the same colony, we included the nest as a random variable (nested into colony; Littell et al. 1996).
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