Extending a popular approach to simulation efficient LFI for single-source data, we propose Multi-objective Bayesian Optimization for Likelihood-Free Inference (MOBOLFI) to estimate the parameters of SSMs calibrated using multi-source data.
Methodology Applications
From a model-based perspective, a probabilistic formalization has been provided by considering a mixture model with component densities following a Wishart distribution.
Methodology
However, a significant challenge in applying such a model is the potential presence of partially observed covariates in the data.
Methodology
Many complex systems in science and engineering are modeled as networks whose nodes and links depict the temporal evolution of each system unit and the dynamic interaction between pairs of units, which are assessed respectively using measures of auto- and cross-correlation or variants thereof.
Methodology
Feature allocation models are an extension of Bayesian nonparametric clustering models, where individuals can share multiple features.
Methodology
We propose a parametric hazard model obtained by enforcing positivity in the damped harmonic oscillator.
Methodology
The overarching goal of this work is to assess the potential for using a more statistically rigorous approach to monitor the risk of political violence and conflict events in practice and characterise their temporal and spatial patterns.
Applications
We introduce Inspection-Guided Randomization (IGR), a transparent and flexible framework for restricted randomization that filters out undesirable treatment assignments by inspecting assignments against analyst-specified, domain-informed design desiderata.
Methodology Applications
The implementation of public policies is crucial in controlling the spread of COVID-19.
Applications
In this article, a new methodology is proposed to estimate time-since-infection dependent recovery and death rates using easily available data sources, accommodating irregular data collection timings reflective of real-world reporting practices.
Applications
