Sentence examples for is a unique probability from inspiring English sources

When qualitative probability relations are defined on a language with a rich enough vocabulary and satisfy one additional axiom, they can be shown to be representable by probability functions i.e., given any qualitative probability relation ⊆, there is a unique probability function P such that A ⊆ B just in case P[A] ≤ P[B].

If (b_{1}+alpha_{1}D_{1}>D_{2}mathrm{e}^{-d_{1}tau_{1}}), (b_{2}+alpha _{2}D_{2}>D_{1}mathrm{e}^{-d_{2}tau_{2}}), then model (4) is asymptotically stable in distribution, that is, as (trightarrow+infty ), for any (xi(t)in C [-tau,0]; R^{2}_)), there is a unique probability measure (v(C [-tau,0]h therethe transision probability density (p(t,xi,cdot)) of (x(t)) converges weakly to (v(cdot)).

Assuming the probability of two DSBs within the span is negligible, these probabilities were summed over all positions within the span 3) where: Given this formulation, there is a unique probability for each span between two unconverted SNPs of distance i and a unique probability for each observed GC.

The irreducible Markov chain is called aperiodic, if for some n ≥ 0 and some state E j, p r o b (X n = E j | X 0 = E j ) > 0 & p r o b (X n + 1 = E j | X 0 = E j ) > 0. If the Markov chain is irreducible and aperiodic then lim t → ∞ p r o b (X t = E j ) = π j         j = 1, …, s such that π = (π1,..., π s) is a unique probability distribution and π j = ∑ i = 1 s π i p i j.

Liu-Bai [26] proposed the concept of stochastically persistent in probability: there is a unique invariant probability measure μ such that (mu(Delta _{0})=0) and the distribution of (X t)) converges to μ as (t rightarrowinfty) whenever (X 0) inmathbb{R}_^{n}), where (Delta _{0}={ainmathbb{R}_^{n}|a_{i}=0mbox{ for some }i, 1leq ileq n}).

As shown in Figure 4, there is a unique optimal transmission probability, p∗, which achieves the maximum throughput.

So, if for some function h the measures μ h n satisfy the compatibility condition, then there is a unique p-adic probability measure, which we denote by μ h, since it depends on h.

Each model parameter was assigned a unique probability distribution based upon published estimates of uncertainty.

52 56 Our inclusion of a mathematical model for predicting probability is a unique attempt to provide quantification of the available evidence based on the Hill criteria.

Since probabilities are objective probabilities, there is a unique SDF, i.e., every agent has the same SDF.

First, we prove that system (2) is asymptotically stable in distribution, that is, there exists a unique probability measure μ such that for every (X(0)in mathbb{R}^{2}_), the transition probability (p t, X(0),cdot)) of (X t)) converges weakly to μ as (trightarrow+infty).