Håkon Tjelmeland
Bakgrunn og aktiviteter
Håkon Tjelmeland er professor ved Institutt for matematiske fag. Han tilhører Gruppen for statistikk. Tjelmeland er utdannet sivilingeniør i industriell matematikk, og har en doktorgrad i statistikk, begge fra NTNU.
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2021) Overestimation of volatility in schizophrenia and autism? A comparative study using a probabilistic reasoning task. PLOS ONE.
- (2020) Psychosis and Psychotic-Like Symptoms Affect Cognitive Abilities but Not Motivation in a Foraging Task. Frontiers in Psychology. vol. 11.
- (2020) Ensemble updating of binary state vectors by maximising the expected number of unchanged components. Scandinavian Journal of Statistics.
- (2019) A multiple-try Metropolis–Hastings algorithm with tailored proposals. Computational statistics (Zeitschrift).
- (2019) Prior specification for binary Markov mesh models. Statistics and computing. vol. 29 (2).
- (2019) A Bayesian model for lithology/fluid class prediction using a Markov mesh prior fitted from a training image. Geophysical Prospecting. vol. 67 (3).
- (2017) Læringsressurser i grunnutdanningen i matematikk - kvalitet, tilgjengelighet og differensiering. Læring om læring. vol. 1.
- (2016) Prior specification of neighbourhood and interaction structure in binary Markov random fields. Statistics and computing.
- (2016) Approximate computations for binary Markov random fields and their use in Bayesian models. Statistics and computing.
- (2015) Fully Bayesian Binary Markov Random Field Models: Prior Specification and Posterior Simulation. Scandinavian Journal of Statistics. vol. 42 (4).
- (2015) Identifying the computational parameters gone awry in psychosis. Lecture Notes in Computer Science (LNCS). vol. 9250.
- (2013) Construction of Binary Multi-grid Markov Random Field Prior Models from Training Images. Mathematical Geosciences. vol. 45 (4).
- (2012) Lithology and fluid prediction from prestack seismic data using a Bayesian model with Markov process prior. Geophysical Prospecting. vol. 60 (3).
- (2012) Near optimal prediction from relevant components. Scandinavian Journal of Statistics. vol. 39 (4).
- (2012) Exact and Approximate Recursive Calculations for Binary Markov Random Fields Defined on Graphs. Journal of Computational And Graphical Statistics. vol. 21 (3).
- (2011) Approximate forward–backward algorithm for a switching linear Gaussian model. Computational Statistics & Data Analysis. vol. 55 (1).
- (2011) Precision and Reliability in Animal Navigation. Bulletin of Mathematical Biology. vol. 73 (5).
- (2010) Bayesian calibration of hydrocarbon reservoir models using an approximate reservoir simulator in the prior specification. Statistical Modelling. vol. 10 (1).
- (2009) Optimal cache search depends on precision of spatial memory and pilfering, but what if that knowledge is not perfect?. Animal Behaviour. vol. 78 (4).
- (2009) A Bayesian model for cross-study differential gene expression. Journal of the American Statistical Association. vol. 104 (488).