Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 28 min ago
PreprintCC BY-NC-ND 4.0arXiv

Interval-Constrained Brownian Paths: Exact Interpolation and Extrapolation

Abstract

We study Brownian motion and Brownian bridge processes conditioned to remain in a fixed interval [0,a], focusing on the conditional distribution at a single time. For a Brownian motion in [0,a], conditioned on survival up to time t we recall (and present in a self-contained form) the conditional density of its position at t (exact extrapolation). For a Brownian bridge conditioned to remain in [0,a] on [0,T] we express the probability density at an interior time as a normalized product of killed transition densities (exact interpolation). These densities admit dual complementary series representations, which are linked via the Jacobi theta identity. Our main contribution is a unified exact sampling suite for both extrapolation and interpolation that (i) includes boundary endpoints and (ii) automatically switches between density representations to keep acceptance rates efficient across regimes. To that end, we derive simple proposal families which cover both small- and large-time regimes, with an automatic rule selecting the tighter envelope. Our procedures extend to exact simulation of discrete skeleton paths at multiple times via the Markov property.

Related

  1. Brownian covariances on an interval: a complete endpoint classification
    Lars Lau Raket
    arXivPreprintCC BY-SA 4.0Full textProbabilityarXiv
  2. Target-Constrained Pooling for Trajectory Extrapolation
    Ning Wang, Claire Cardie, Sainyam Galhotra
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  3. Lp-extrapolation via non-local decay estimates: theory and applications to the generalized Stokes operator with rough coefficients
    Luca Haardt
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsarXiv
  4. Smooth periodic extensions by extrapolation and blending for FFT-based differentiation
    Ivan Méndez-Cruz, Faisal Amlani
    HALPreprintCC BY 4.0Full textNumerical analysis & scientific computingHALarXiv
  5. New matrix-weighted norm inequalities and extrapolation
    Guixiang Hong, Pengfei Yin
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsarXiv
BibTeX
@misc{herbei2026intervalconstrained,
  title = {{Interval-Constrained Brownian Paths: Exact Interpolation and Extrapolation}},
  author = {Radu Herbei and Kumar Somnath},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.21943},
  eprint = {2609.21943},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.21943},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - UNPB
TI  - Interval-Constrained Brownian Paths: Exact Interpolation and Extrapolation
AU  - Radu Herbei
AU  - Kumar Somnath
PY  - 2026
DA  - 2026/09/18
PB  - arXiv
DO  - 10.48550/arxiv.2609.21943
UR  - https://arxiv.org/abs/2609.21943
AB  - We study Brownian motion and Brownian bridge processes conditioned to remain in a fixed interval [0,a], focusing on the conditional distribution at a single time. For a Brownian motion in [0,a], conditioned on survival up to time t we recall (and present in a self-contained form) the conditional density of its position at t (exact extrapolation). For a Brownian bridge conditioned to remain in [0,a] on [0,T] we express the probability density at an interior time as a normalized product of killed transition densities (exact interpolation). These densities admit dual complementary series representations, which are linked via the Jacobi theta identity. Our main contribution is a unified exact sampling suite for both extrapolation and interpolation that (i) includes boundary endpoints and (ii) automatically switches between density representations to keep acceptance rates efficient across regimes. To that end, we derive simple proposal families which cover both small- and large-time regimes, with an automatic rule selecting the tighter envelope. Our procedures extend to exact simulation of discrete skeleton paths at multiple times via the Markov property.
ER  -