Asymptotic independence conjecture for fractional weights in stratified resampling
Asymptotic independence conjecture for fractional weights in stratified resampling
Let , let be continuous, and let . For the step- particles , define
Let denote the normalized stratified-resampling weights. Fractional-weight convergence conjecture. The difference between the two expectations obtained by evaluating at and by averaging its first argument uniformly over converges to zero after summing over and dividing by :
\begin{aligned} &\left|\frac{1}{M}\sum_{m=1}^{M-t}\mathbb{E}\left[h(X_n^{M,m},\ldots,X_n^{M,m+t})\psi(\nu_n^{M,m-1},w_n^{M,m},\ldots,w_n^{M,m+t})\right]\\ &-\frac{1}{M}\sum_{m=1}^{M-t}\mathbb{E}\left[h(X_n^{M,m},\ldots,X_n^{M,m+t})\int_0^1\psi(u,\widetilde g_n(X_n^{M,m}),\ldots,\widetilde g_n(X_n^{M,m+t}))\,du\right]\right|\longrightarrow0. \end{aligned}This is the multi-step analogue of the fractional-part convergence used for the initial resampling step and underlies the recursive variance analysis. The source gives no proof or resolution of this convergence.
Sources & referencesView supporting material
Primary source
Roberta Flenghi and Benjamin Jourdain, “Central limit theorem for the stratified resampling mechanism”, arXiv:2308.02186 (2023).
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