bayesilainen menetelmä

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• bayesilainen menetelmä

Works about bayesilainen menetelmä

• Accident probabilities in selected areas of the Gulf of Finland
• Addressing human-induced uncertainty in fisheries management : social scientific and interdisciplinary solutions using Bayesian belief networks
• Analysis of human and organizational factors in marine traffic risk modeling : literature review
• Application of decision-analytic modelling in health economic evaluations
• Approximate Bayesian inference methods for regression and classification with Gaussian processes and neural networks
• Approximate Bayesian inference methods for stochastic state space models
• Approximation strategies for structure learning in Bayesian networks
• Assessing oil spill risks in the northern Baltic Sea with Bayesian network applications
• Bayesian analysis of SEIR epidemic models
• Bayesian cluster analysis with applications to pathogen population genomics
• Bayesian filtering and smoothing
• Bayesian fisheries stock assessment : integrating and updating knowledge
• Bayesian inference for spatio-temporal models
• Bayesian latent Gaussian spatio-temporal models
• Bayesian latent variable models for learning dependencies between multiple data sources
• Bayesian methods for exploring structure in time series
• Bayesian methods in insurance companies' risk management
• Bayesian models for the reconstruction of the paleoclimate
• Bayesian multi-view models for data-driven drug response analysis
• Bayesian multilocus association models for prediction and mapping of genome-wide data
• Bayesian Network applications for environmental risk assessment
• Bayesian network modeling of potential patterns in maritime safety performance
• Bayesian networks : an introduction
• Bayesian spatial and temporal epidemiology of non-communicable diseases and mortality
• Bayesian statistical analysis of bacterial diversity
• Computational optimization methods for large-scale inverse problems
• Edge-promoting priors in electrical impedance tomography
• Electrical resistance tomography imaging of concrete
• Embracing uncertainty in fisheries stock assessment using Bayesian hierarchical models
• Image reconstruction with error modelling in diffuse optical tomography
• Kuka päättää geenitutkimuksiin osallistumisesta? : normatiivinen ja sosiologinen analyysi bayesilaisen menetelmän kelpoisuudesta avuksi
• Learning discriminative models from structured multi-sensor data for human context recognition
• Miksi monet ennusteet epäonnistuvat, mutta jotkin eivät
• Model-based decision processes for agenda building and project funding
• Model-based efficiency analyses of healthcare delivery
• Model-based structural damage identification using vibration measurements
• Modeling of professional growth and learning : Bayesian approach
• Modelling errors in electrical impedance tomography
• Multivariate multi-way modelling of multiple high-dimensional data sources
• Nowcasting the unemployment rate in the EU with seasonal BVAR and Google search data
• Nurse staffing and nursing outcome in a complex acute health care system
• On Bayesian predictive modeling : with applications on the analysis of chromatography data in forensic investigations
• On model selection for Bayesian networks and sparse logistic regression
• Probabilistic components of molecular interactions and drug responses
• Probabilistic contact preferences in protein-ligand and protein-protein complexes
• Statistical modelling of selective non-participation in health examination surveys
• Statistical studies on bacterial transmission and community dynamics with a special emphasis on the colonization dynamics of Streptococcus pneumoniae during early childhood
• Steps towards comprehensive Bayesian decision analysis in fisheries and environmental management
• Steps towards comprehensive decision analysis in fisheries and environmental management
• Structure learning of context-specific graphical models
• The most probable Bayesian network and beyond
• The time series convergence of dispersion in financial analysts' forecasts
• Training methods for climate and neural network models
• Uncertainty quantification in remote sensing of forests
• Use of secondary structures in the analysis of spatial point patterns
• Water quality prediction for river basin management