320 citations · 760 across the 27 of their papers we have counts for
3 papers · 2 filters
panelPomp: Analysis of Panel Data via Partially Observed Markov Processes in R
Carles Bretó, Jesse Wheeler, Aaron A. King +1
Panel data arise when time series measurements are collected from multiple, dynamically independent but structurally related systems. Each system's time series can be modeled as a…
Poisson approximate likelihood compared to the particle filter
Yize Hao, Aaron A. Abkemeier, Edward L. Ionides
Filtering algorithms are fundamental for inference on partially observed stochastic dynamic systems, since they provide access to the likelihood function and hence enable likelihoo…
Accelerated Inference for Partially Observed Markov Processes using Automatic Differentiation
Kevin Tan, Giles Hooker, Edward L. Ionides
Automatic differentiation (AD) has driven recent advances in machine learning, including deep neural networks and Hamiltonian Markov Chain Monte Carlo methods. Partially observed n…