Sentence examples for a sequence of measures from inspiring English sources

Classical, single-level SMC constructs a sequence of measures, starting with the prior distribution, and finishing with the posterior distribution.

Also, we showed that the support of such a measure is the attractor of the given GIFSp and we construct a sequence of measures converging to this measure.

Let ({varvec{nu }}={nu _j}_{j=0}^infty ) be a sequence of measures such that each (nu _j) is a quadrature measure of order (2^{j+1}).

Further, let ({varvec{mu }}={mu _j}_{j=0}^infty ) be a sequence of measures such that each (mu _j) is an M Z quadrature measure of order (3 times 2^{j-1}).

We say a sequence of measures ( {varvec{mu }}= left{ mu _n right} ) has nested support when begin{aligned} m < n implies mathsf{supp }(mu _m) subseteq mathsf{supp }(mu _n).

end{aligned}In addition to the centers, we will assume in the remainder of this and the next subsection that ({varvec{mu }}={mu _j}_{j=0}^infty ) is a sequence of measures such that each (mu _j) is an M Z quadrature measure of order (3times 2^{j-1}).

Uncoated and TiN coated mixed oxide ceramics inserts have been tested concerning their microgeometry and wear resistance and there is presented a sequence of measuring to identify cutting edge preparation and properties of coating.

Sequential Monte Carlo (SMC) samplers [Del Moral, P., Doucet, A., Jasra, A., 2006. Sequential Monte Carlo samplers. J. Roy. Statist. Soc. B 68, 411 436] are designed to simulate from a sequence of probability measures on a common measurable space (E,E).

In [11, 12], Crovisier explained Mañé's ergodic closing lemma which gives the measure theoretical viewpoint on the approximation by periodic orbit, that is, any ergodic invariant probability measure μ of C1-generic Diffeomorphism is the limit of a sequence of invariant measures supported by periodic orbits O f ( p n ).

Let {p n } n∈ℕbe a sequence of signed measures in B ̄ r ( 0 ), and {p n } n∈ℕconverges to a signed measure p. In case E ∈ M z, E ⊂ x 0 z ¯, using dominated convergence theorem lim B p n ( E ) = lim n → ∞ ∫ E g ( x, p n ( S ̄ x ), p n ( S ̄ x ω ) ) d μ = ∫ E g ( x, p ( S ̄ x ), p ( S ̄ x ω ) ) d μ = B p ( E ).

The estimates (3.45) are more general in the sense that the sequence ({varvec{mu }}) can be a sequence of discrete measures as well, in which case, the values of (f) at the points in the supports of these measures are used.