4 papers
Hybrid physics-data driven spectral forecasts of semisubmersible response
Ian Milne, Lachlan Astfalck, Matthew Zed +2
A framework for probabilistic forecasting of vessel motion is developed and validated for a semisubmersible operating in long period swell. Bayesian statistical methods are applied…
Efficient Bayesian Inference for Discretely Observed Continuous Time Markov Chains
Tao Tang, Lachlan Astfalck, David Dunson
Inference for continuous-time Markov chains (CTMCs) becomes challenging when the process is only observed at discrete time points. The exact likelihood is intractable, and existing…
Universal Modelling of Autocovariance Functions via Spline Kernels
Lachlan Astfalck
Flexible modelling of the autocovariance function (ACF) is central to time-series, spatial, and spatio-temporal analysis. Modern applications often demand flexibility beyond classi…
Bias correction of quadratic spectral estimators
Lachlan Astfalck, Adam Sykulski, Edward Cripps
The three cardinal, statistically consistent, families of non-parametric estimators to the power spectral density of a time series are lag-window, multitaper and Welch estimators.…