35 citations · 59 across the 5 of their papers we have counts for
5 papers
Hierarchical Bayesian propulsion power models for marine vessels
Antti Solonen, Ramona Maraia, Sebastian Springer +5
Assessing the magnitude of fuel consumption of marine traffic is a challenging task. The consumption can be reduced by the ways the vessels are operated, to achieve both improved c…
Introduction to Dynamic Linear Models for Time Series Analysis
Marko Laine
Dynamic linear models (DLM) offer a very generic framework to analyse time series data. Many classical time series models can be formulated as DLMs, including ARMA models and stand…
Likelihood informed dimension reduction for inverse problems in remote sensing of atmospheric constituent profiles
Otto Lamminpää, Marko Laine, Simo Tukiainen +1
We use likelihood informed dimension reduction (LIS) (T. Cui et al. 2014) for inverting vertical profile information of atmospheric methane from ground based Fourier transform infr…
Shape recovery from sparse tomographic X-ray data
Heikki Haario, Aki Kallonen, Marko Laine +3
A two-dimensional tomographic problem is studied. The target is assumed to be a homogeneous object bounded by a smooth curve. A Non Uniform Rational Basis Splines (NURBS) curve is…
Bayesian Principal Component Regression model with spatial effects for forest inventory under small field sample size
Virpi Junttila, Marko Laine
Remote sensing observations are extensively used for analysis of environmental variables. These variables often exhibit spatial correlation, which has to be accounted for in the ca…