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}).
Besides, the solution set is continuous with respect to the data, in the sense that when a sequence of measures ( μ i ) tends to μ in the weak∗ topology (cf. [10]), for any sequence ( x i ) of robust solutions corresponding to μ i there exists a robust solution x corresponding to μ with the property that on a subsequence x i → x ( weakly ∗ ) and x i ( t ) → x ( t ) except on the atoms of μ.
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).
We will deal with two different sequences of measures; the sequence ({{varvec{nu }}}) will be a sequence of discrete measures, whose supports will give us the centers of the networks, and the sequence ({{varvec{mu }}}) will be the sequence of measures so that the information on the target function is given in terms of integrals with respect to the members of this sequence.
Under all these modes, the client establishes a sequence of HTTP connections, measuring the resulting RTT.
