2 citations · 4 across the 3 of their papers we have counts for
4 papers
AeroMig: Multi-modal Inverse-Gamma modeling for aerosol particle number size distributions
Abdur Rahman, Juha Kangasluoma, Santtu Mikkonen +4
Aerosol particles play a critical role in air quality, human health, and climate processes, making their accurate characterization essential. One common way to represent aerosol po…
Artificial Intelligence for Atmospheric Sciences: A Research Roadmap
Martha Arbayani Zaidan, Naser Hossein Motlagh, Petteri Nurmi +4
Atmospheric sciences are crucial for understanding environmental phenomena ranging from air quality to extreme weather events, and climate change. Recent breakthroughs in sensing,…
Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions
Darren Wraith, Kerrie Mengersen, Clair Alston +2
The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared usi…
Bayesian semi-parametric forecasting of ultrafine particle number concentration with penalised splines and autoregressive errors
Sam Clifford, Bjarke Mølgaard, Sama Low Choy +4
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for flexible regression mod…