Nils Lid Hjort

• Dæhlen, Ingrid; Hjort, Nils Lid & Haff, Ingrid Hobæk (2023). Accurate bias estimation with applications to focused model selection. Scandinavian Journal of Statistics. ISSN 0303-6898. s. 1–36. doi: 10.1111/sjos.12696. Fulltekst i vitenarkiv
• Aastveit, Marthe Elisabeth; Cunen, Celine Marie Løken & Hjort, Nils Lid (2023). A new framework for semi-Markovian parametric multi-state models with interval censoring. Statistical Methods in Medical Research. ISSN 0962-2802. 32(6), s. 1053–1246. doi: 10.1177/09622802231160550. Fulltekst i vitenarkiv Vis sammendrag

  There are few computational and methodological tools available for the analysis of general multi-state models with interval censoring. Here, we propose a general framework for parametric inference with interval censored multi-state data. Our framework can accommodate any parametric model for the transition times, and covariates may be included in various ways. We present a general method for constructing the likelihood, which we have implemented in a ready-to-use R package, smms, available on GitHub. The R package also computes the required high-dimensional integrals in an efficient manner. Further, we explore connections between our modelling framework and existing approaches: our models fall under the class of semi-Markovian multi-state models, but with a different, and sparser parameterisation than what is often seen. We illustrate our framework through a dataset monitoring heart transplant patients. Finally, we investigate the effect of some forms of misspecification of the model assumptions through simulations.

• Cunen, Celine & Hjort, Nils Lid (2021). Combining information across diverse sources: The II-CC-FF paradigm. Scandinavian Journal of Statistics. ISSN 0303-6898. s. 1–32. doi: 10.1111/sjos.12530. Fulltekst i vitenarkiv
• Hjort, Nils Lid & Stoltenberg, Emil Aas (2021). The partly parametric and partly nonparametric additive risk model. Lifetime Data Analysis. ISSN 1380-7870. doi: 10.1007/s10985-021-09535-3. Fulltekst i vitenarkiv Vis sammendrag

  Aalen’s linear hazard rate regression model is a useful and increasingly popular alternative to Cox’ multiplicative hazard rate model. It postulates that an individual has hazard rate function h(s)=z1α1(s)+⋯+zrαr(s) in terms of his covariate values z1,…,zr. These are typically levels of various hazard factors, and may also be time-dependent. The hazard factor functions αj(s) are the parameters of the model and are estimated from data. This is traditionally accomplished in a fully nonparametric way. This paper develops methodology for estimating the hazard factor functions when some of them are modelled parametrically while the others are left unspecified. Large-sample results are reached inside this partly parametric, partly nonparametric framework, which also enables us to assess the goodness of fit of the model’s parametric components. In addition, these results are used to pinpoint how much precision is gained, using the parametric-nonparametric model, over the standard nonparametric method. A real-data application is included, along with a brief simulation study.

• Cunen, Celine; Walløe, Lars; Konishi, Kenji & Hjort, Nils Lid (2021). Decline in body condition in the Antarctic minke whale (Balaenoptera bonaerensis) in the Southern Ocean during the 1990s. Polar Biology. ISSN 0722-4060. 44, s. 259–273. doi: 10.1007/s00300-020-02783-3. Fulltekst i vitenarkiv
• Cunen, Celine; Walløe, Lars & Hjort, Nils Lid (2020). Focused model selection for linear mixed models with an application to whale ecology. Annals of Applied Statistics. ISSN 1932-6157. 14(2). doi: 10.1214/20-AOAS1331. Fulltekst i vitenarkiv
• Cunen, Celine; Hjort, Nils Lid & Schweder, Tore (2020). Confidence in confidence distributions! Proceedings of the Royal Society. Mathematical, Physical and Engineering Sciences. ISSN 1364-5021. doi: 10.1098/rspa.2019.0781. Fulltekst i vitenarkiv
• Cunen, Celine & Hjort, Nils Lid (2020). Confidence Distributions for FIC Scores. Econometrics. ISSN 2225-1146. 8(27). doi: 10.3390/econometrics8030027. Fulltekst i vitenarkiv
• Stoltenberg, Emil Aas & Hjort, Nils Lid (2020). Models and inference for on–off data via clipped Ornstein–Uhlenbeck processes. Scandinavian Journal of Statistics. ISSN 0303-6898. doi: 10.1111/sjos.12472. Fulltekst i vitenarkiv
• Cunen, Celine Marie Løken; Hjort, Nils Lid & Nygård, Håvard Mokleiv (2020). Statistical sightings of better angels: Analysing the distribution of battle-deaths in interstate conflict over time. Journal of Peace Research. ISSN 0022-3433. 57(2), s. 221–234. doi: 10.1177/0022343319896843. Fulltekst i vitenarkiv
• Stoltenberg, Emil Aas & Hjort, Nils Lid (2019). Multivariate estimation of Poisson parameters. Journal of Multivariate Analysis. ISSN 0047-259X. 175, s. 1–19. doi: 10.1016/j.jmva.2019.104545. Fulltekst i vitenarkiv
• Claeskens, Gerda; Cunen, Celine Marie Løken & Hjort, Nils Lid (2019). Model Selection via Focused Information Criteria for Complex Data in Ecology and Evolution. Frontiers in Ecology and Evolution. ISSN 2296-701X. 7. doi: 10.3389/fevo.2019.00415. Fulltekst i vitenarkiv
• Walløe, Lars; Hjort, Nils Lid & Thoresen, Marianne (2019). Why results from Bayesian Statistical analyses of clinical trials with a strong prior and small sample sixes may be misleading. Acta Paediatrica. ISSN 0803-5253. s. 1190–1191. doi: 10.1111/apa.14800. Fulltekst i vitenarkiv
• Walløe, Lars; Hjort, Nils Lid & Thoresen, Marianne (2019). Start cooling as soon as possible. Acta Paediatrica. ISSN 0803-5253. 108(4), s. 771–771. doi: 10.1111/apa.14710.
• Ko, Vinnie; Hjort, Nils Lid & Hobæk Haff, Ingrid (2019). Focused information criteria for copulae. Scandinavian Journal of Statistics. ISSN 0303-6898. 46, s. 1117–1140. doi: 10.1111/sjos.12387. Fulltekst i vitenarkiv
• Ko, Vinnie & Hjort, Nils Lid (2019). Model robust inference with two-stage maximum likelihood estimation for copulas. Journal of Multivariate Analysis. ISSN 0047-259X. 171, s. 362–381. doi: 10.1016/j.jmva.2019.01.004. Fulltekst i vitenarkiv
• Ko, Vinnie & Hjort, Nils Lid (2019). Copula information criterion for model selection with two-stage maximum likelihood estimation. Econometrics and Statistics. ISSN 2452-3062. 12, s. 167–180. doi: 10.1016/j.ecosta.2019.01.001. Fulltekst i vitenarkiv
• Hjort, Nils Lid & Sørensen, Øystein (2018). Rikdom og pengenes verdi i Andeby. Donald Duck & Co.
• Walløe, Lars; Hjort, Nils Lid & Thoresen, Marianne (2018). Major concerns about late hypothermia study. Acta Paediatrica. ISSN 0803-5253. doi: 10.1111/apa.14640. Fulltekst i vitenarkiv
• Jullum, Martin & Hjort, Nils Lid (2018). What price semiparametric Cox regression? Lifetime Data Analysis. ISSN 1380-7870. 25(3), s. 406–438. doi: 10.1007/s10985-018-9450-7. Fulltekst i vitenarkiv
• Hellton, Kristoffer Herland & Hjort, Nils Lid (2018). Fridge: Focused fine‐tuning of ridge regression for personalized predictions. Statistics in Medicine. ISSN 0277-6715. 37(8), s. 1290–1303. doi: 10.1002/sim.7576. Fulltekst i vitenarkiv Vis sammendrag

  Statistical prediction methods typically require some form of fine‐tuning of tuning parameter(s), with K‐fold cross‐validation as the canonical procedure. For ridge regression, there exist numerous procedures, but common for all, including cross‐validation, is that one single parameter is chosen for all future predictions. We propose instead to calculate a unique tuning parameter for each individual for which we wish to predict an outcome. This generates an individualized prediction by focusing on the vector of covariates of a specific individual. The focused ridge—fridge—procedure is introduced with a two‐part contribution: First we define an oracle tuning parameter minimizing the mean squared prediction error of a specific covariate vector, and then we propose to estimate this tuning parameter by using plug‐in estimates of the regression coefficients and error variance parameter. The procedure is extended to logistic ridge regression by using parametric bootstrap. For high‐dimensional data, we propose to use ridge regression with cross‐validation as the plug‐in estimate, and simulations show that fridge gives smaller average prediction error than ridge with cross‐validation for both simulated and real data. We illustrate the new concept for both linear and logistic regression models in two applications of personalized medicine: predicting individual risk and treatment response based on gene expression data. The method is implemented in the R package fridge.

• Hjort, Nils Lid; McKeague, Ian & Van Keilegom, Ingrid (2018). Hybrid combinations of parametric and empirical likelihoods. Statistica sinica. ISSN 1017-0405. 28(4), s. 2389–2407. doi: 10.5705/ss.202017.0291. Fulltekst i vitenarkiv
• Cunen, Celine Marie Løken; Hermansen, Gudmund Horn & Hjort, Nils Lid (2018). Confidence distributions for change-points and regime shifts. Journal of Statistical Planning and Inference. ISSN 0378-3758. 195, s. 14–34. doi: 10.1016/j.jspi.2017.09.009. Fulltekst i vitenarkiv
• Hjort, Nils Lid & Schweder, Tore (2017). Confidence distributions and related themes. Journal of Statistical Planning and Inference. ISSN 0378-3758. 195, s. 1–13. doi: 10.1016/j.jspi.2017.09.017.
• Jullum, Martin & Hjort, Nils Lid (2017). Parametric or nonparametric: The FIC approach. Statistica sinica. ISSN 1017-0405. 27(3), s. 951–981. doi: 10.5705/ss.202015.0364. Vis sammendrag

  Should one rely on a parametric or nonparametric model when analysing a given data set? This classic question cannot be answered by traditional model selection criteria like AIC and BIC, since a nonparametric model has no likelihood. The purpose of the present paper is to develop a focused information criterion (FIC) for comparing general non-nested parametric models with a nonparametric alternative. It relies in part on the notion of a focus parameter, a population quantity of particular interest in the statistical analysis. The FIC compares and ranks candidate models based on estimated precision of the different model-based estimators for the focus parameter. It has earlier been developed for several classes of problems, but mainly involving parametric models. The new FIC, including also nonparametrics, is novel also in the mathematical context, being derived without the local neighbourhood asymptotics underlying previous versions of FIC. Certain average-weighted versions, called AFIC, allowing several focus parameters to be considered simultaneously, are also developed. We concentrate on the standard i.i.d. setting and certain direct extensions thereof, but also sketch further generalisations to other types of data. Theoretical and simulation-based results demonstrate desirable properties and satisfactory performance.

• Glad, Ingrid Kristine & Hjort, Nils Lid (2016). Model uncertainty first, not afterwards. Statistical Science. ISSN 0883-4237. 31(4), s. 490–494. doi: 10.1214/16-STS559. Fulltekst i vitenarkiv

Se alle arbeider i Cristin

• Hjort, Nils Lid (2023). How Many Were Killed in Guatemala, 1978 to 1996? Counting the Uncounted. Vis sammendrag

  The task of estimating N000, the unseen individuals.

• Hjort, Nils Lid (2023). Ongoing Themes and Activities for the Stability and Change Project Group. Vis sammendrag

  Håvard Hegre and Nils Lid Hjort presented ongoing themes and activities, to the general CAS audience, in their project Stability and Change.

• Hjort, Nils Lid (2023). The Window of Change. Vis sammendrag

  The Window of Change, talk at the ChangeTrend Workshop, organised via CAS and its programme Stability and Change, August 2022 to June 2023, led by Hegre and Hjort.

• Hjort, Nils Lid (2023). Does Polity Score Influence Size of War and Probability of Conflict Escalation? Vis sammendrag

  From the DemoIndex Workshop, organised via the CAS programme Stability and Change, August 2022 to June 2023, led by Hjort and Hegre.

• Hjort, Nils Lid (2023). Bayes, Confidence Distributions, and US Pre-War Economy. Vis sammendrag

  Invited talk at the NSF Oslo årsmøte, May 2023. I disagree with Sims, the winner of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, regarding his methods and conclusions in his Nobel Prize acceptance lecture. We had pizza afterwards.

• Hjort, Nils Lid & Cunen, Celine Marie Løken (2023). Independent Inspection, Confidence Conversion, Focused Fusion: Combining (Very) Different Information Sources. Vis sammendrag

  Invited talk at the Nordic-Baltic Biometric Conference, Göteborg, June 2023. I presented the II-CC-FF paradigm, joint work with Celine Cunen.

• Hjort, Nils Lid (2023). How many were killed in Guatemala, 1978-1996? A FIC for N. Vis sammendrag

  Talk in the section on model selection at NordStat 2023, Göteborg. The slides are available at the FocuStat site. The work relates to the Stability and Change programme at CAS, August 2022 to June 2023, led by Hjort and Hegre.

• Hjort, Nils Lid & Tveite, Tor (2023). Konsert under Nissedal VokalFestival, Nissedal, 27.-29. juli 2023. Festivalkvartetten bestod av Hege Gustava Tjønn Ludwig (sopran), Kjersti Svärd Løberg (alt), Tor Tveite (tenor), Nils Lid Hjort (bass). Vi var definert som festivalkunstnere. Vis sammendrag

  Festivalkunstneren for Nissedal VokalFestival 2023 var Tor Tveite. En solokvartett, bestående av Hege Gustava Tjønn Ludwig, Kjersti Svärd Løberg, Tor Tveite, Nils Lid Hjort, fremførte flere av hans verker.

• Hjort, Nils Lid (2023). Oljeeventyret -- i Norge og i Andeby. Donald Duck & Co. 9(Norsk Donald (bokserie)), s. 4–9. Vis sammendrag

  "Oljeeventyret - i Norge og i Andeby", invitert forord i bind 9 i bokserien "Donald på norsk", utgitt av Egmont, 2023. Cristin har ikke pre-lagret denne bokserien, eller forlaget, så hun tillater meg ikke å registrere dette som populærvitenskapelig bidrag i en bok, og det blir irriterende nok stående, inntil videre, som bidrag i Donald Duck & Co., altså bladet, eller tidsskriftet.

• Christensen, Dennis; Unneberg, Erik; Høyheim, Eirik; Jensen, Tomas Lunde & Hjort, Nils Lid (2023). Improved measurements of impact sensitivities of energetic materials. Vis sammendrag

  Accurate estimation of impact sensitivity is crucial for safe production, handling, storage and transport of energetic materials. Indeed, molecular characteristics will affect sensitivity, and for solid materials, factors like particle size, lattice defects and morphology also play a role and make reproducibility difficult. As various synthesis and recrystallisation methods may lead to differences in crystal properties, it is important to determine the impact sensitivity whenever an energetic material is prepared. Of particular interest is the median ℎ50, namely the impact energy level at which there is a probability of 50% of an explosion occurring. This value has been shown to correlate with quantum chemical properties of the energetic material in question, providing insight into the underlying causes which govern sensitivity. However, in practical applications, it may be more important to estimate extreme values like the 99% quantile ℎ99. In addition to providing point estimates, we would like to derive confidence intervals to address their uncertainty. In this work, we cover the most common methods for constructing such confidence intervals (the delta method, Fieller’s theorem and the likelihood-ratio test) and compare their performance on sensitivity data via simulations. Our experiments indicate that Fieller’s theorem is the superior method, and we therefore use it to construct confidence intervals for ℎ50 and ℎ99 for cyclotetramethylene- tetranitramine (HMX), using new data. Based on our results, we formulate recommendations for researchers measuring sensitivities of synthesised molecules.

• Hjort, Nils Lid & Stoltenberg, Emil Aas (2022). The partly parametric and partly nonparametric additive risk model. Vis sammendrag

  Invited talk at the Ørnulf Borgan emeritus celebration seminar, Nils Lid Hjort presenting work based on joint work with Emil Stoltenberg.

• Hjort, Nils Lid (2022). Topics in Spatial Statistics (with Henning as my boss), invited talk at the Henning Omre Emeritus celebration.
• Hjort, Nils Lid (2022). Processes With Steadily Rarer but Steadily Bigger Shocks. Vis sammendrag

  Invited talk at the Bo Lindqvist emeritus celebration meeting.

• Hjort, Nils Lid (2022). From Processes to Models: a few sets of ideas.
• Hjort, Nils Lid (2022). Why, when, and how to disobey your government's instructions and save 15,000 lives. Vis sammendrag

  Impromptu talk at the impromptu excursion, during the CAS Workshop Prediction With Uncertainty, to the workshop participants, fifty metres away from the workshop room, to the White Buses, in front of Wanda Hjort Heger painting.

• Hjort, Nils Lid (2022). Prediction With Uncertainty.
• Cunen, Celine & Hjort, Nils Lid (2021). Combining information across diverse studies: the II-CC-FF paradigm.
• Røislien, Jo & Hjort, Nils Lid (2021). Abels kjeller - kortstokkproblemet. [Radio]. NRK Radio - Abels tårn. Vis sammendrag

  Aslak fant ett kort på gata. Så et til. Hvor mange må han finne før han har en komplett kortstokk? Dette tilsynelatende enkle problemet satt fast panelets statistiker da han prøvde seg på det, seint på kvelden før sendinga 18. juni. Men tårnets enestående lyttere kasta seg over problemet og fant riktig svar. I denne kjellerepisoden graver vi oss ned i dypet av problemet, diskuterer analytiske vs. simulerte løsninger, og ender opp med å bestemme rekkefølgen av Platons sokratiske dialoger med statistisk metode. Panelet: Statistikerene Jo Røislien og Nils Lid Hjort Lytterpanelet: Andreas Hafver, Pål Kjeldsen og Tor Inge Birkenes Lønmo

• Cunen, Celine & Hjort, Nils Lid (2019). Gamma process models for survival and competing risks.
• Nygård, Håvard Mokleiv; Cunen, Celine Marie Løken & Hjort, Nils Lid (2019). Blir verden egentlig fredeligere? Aftenposten Viten. ISSN 2464-3033.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2018). Statistical Sightings of Better Angels.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2018). II-CC-FF: Combination of information beyond meta-analysis.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2018). Whales, politics, and statisticians.
• Walker, Sam-Erik & Hjort, Nils Lid (2018). Focused model selection and inference using robust estimators.
• Hjort, Nils Lid (2018). One Thousand is Unfair, Two Thousand is Fair.
• Hjort, Nils Lid (2018). Welcoming remarks & introduction to the FocuStat VVV themes.
• Hjort, Nils Lid (2018). Survival and event history models via Gamma processes (VVV conference).
• Hjort, Nils Lid (2018). Prediction and Confidence (NordStat2018).
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2018). Statistical Sightings of Better Angels (invited seminar).
• Hjort, Nils Lid (2018). Olympic unfairness -- analysing 2 x 1000 m speedskating races. FocuStat Combo Kitchen.
• Hjort, Nils Lid (2018). The Best Metal-Grabbing Games Ever (FocuStat Blog).
• Hjort, Nils Lid (2018). Belgium Breaks a 48 Year Old Curse (Apparently) (FocuStat Blog Post).
• Hjort, Nils Lid (2018). Overdispersed Children (FocuStat Blog Post).
• Jullum, Martin & Hjort, Nils Lid (2018). Parametric or nonparametric, that’s the question.
• Ørstavik, Iver; Hjelseth, Arve & Hjort, Nils Lid (2018). Å fjerne allround på skøyter er som å endre reglene i fotball for å legge opp til flere mål. VG : Verdens gang. ISSN 0805-5203.
• Hjort, Nils Lid (2018). Towards a More Peaceful World [insert `!' or `?' here].
• Hjort, Nils Lid & Cunen, Celine Marie Løken (2018). Whales, Politics, and Statistician (FocuStat Blog Post).
• Hjort, Nils Lid (2018). Towards a More Peaceful World [insert `!' or `?' here] (FocuStat Blog Post).
• Hjort, Nils Lid & Cunen, Celine Marie Løken (2017). New statistical methods shed light on medieval literary mystery (FocuStat Blog Post).
• Hjort, Nils Lid (2017). Cooling of Newborns and the Difference Between 0.244 and 0.278 (FocuStat Blog Post).
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2017). Combining diverse information sources with the II-CC-FF paradigm.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2017). Combining diverse information sources with the II-CC-FF paradigm: Independent Inspection, Confidence Conversion, Focused Fusion.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2017). Combining diverse information sources with the II-CC- FF paradigm.
• Cunen, Celine Marie Løken & Hjort, Nils Lid (2017). Confidence distributions: A potential bridge for combining parametric and nonparametric analyses.
• Cunen, Celine Marie Løken; Walløe, Lars & Hjort, Nils Lid (2017). Decline in energy storage in Antarctic Minke whales during the JARPA period: Assessment via the Focused Information Criterion (FIC).
• Walker, Sam-Erik & Hjort, Nils Lid (2017). Estimation and model selection by data-driven weighted likelihoods.
• Walker, Sam-Erik & Hjort, Nils Lid (2017). Estimation and model selection by data-driven weighted likelihoods.
• Walker, Sam-Erik & Hjort, Nils Lid (2017). Estimation and model selection via maximum weighted likelihoods.
• Walker, Sam-Erik & Hjort, Nils Lid (2017). Focused model selection and inference using robust estimators.
• Hjort, Nils Lid (2017). But some are more equal than others (FocuStat Blog Post).
• Hjort, Nils Lid (2017). The semifinals factor for skiing fast in the finals (FocuStat Blog Post).
• Hjort, Nils Lid (2017). Ut på tur: NordStat, København, juni 2016 (FocuStat Blog Post).
• Hjort, Nils Lid (2017). All models are wrong, but some are more biologically plausible than other: Survival analysis models based on crossing times for cumulative damage processes.
• Hjort, Nils Lid (2017). Confidence distributions for change-points and regime shifts (again).
• Hjort, Nils Lid (2017). Empirical Likelihood and Bayesian Nonparametrics.
• Hjort, Nils Lid (2017). The semifinals factor for skiing fast in the finals.
• Hjort, Nils Lid (2017). The hybrid likelihood.
• Hjort, Nils Lid (2017). Minimum Dispair, Maximum Despair.
• Hjort, Nils Lid (2017). Building Bridges (at Bislett): general workshop themes.
• Hjort, Nils Lid (2017). Data fusion with confidence curves: The II-CC-FF paradigm.
• Hjort, Nils Lid (2017). A gentle introduction to Bayesian Nonparametrics.
• Hjort, Nils Lid (2017). Model selection and model averaging (two hours).
• Hjort, Nils Lid (2017). Confidence distributions and data fusion (two hours).
• Hjort, Nils Lid (2017). Bayesian nonparametrics (two hours).
• Hellton, Kristoffer Herland & Hjort, Nils Lid (2017). Fridge: focused fine-tuning of ridge regression for personalized prediction.
• Hjort, Nils Lid (2016). Recruitment Dynamics and Stock Variability: The Johan Hjort Symposium, some personal reflections (FocuStat Blog Post).
• Walker, Sam-Erik & Hjort, Nils Lid (2016). Model selection and focused inference using robust estimators.
• Walker, Sam-Erik & Hjort, Nils Lid (2016). Model selection and focused inference using robust estimators.
• Hjort, Nils Lid (2016). Recruitment Dynamics and Stock Variability: The Johan Hjort Symposium, some personal reflections. Vis sammendrag

  FocuStat Blog

• Hjort, Nils Lid (2016). Post-Selection Distributions, Model Averaging, Bagging, Inference.
• Tveten, Martin; Glad, Ingrid Kristine & Hjort, Nils Lid (2021). Scalable change and anomaly detection in cross-correlated data. Universitetet i Oslo. Fulltekst i vitenarkiv
• Nygård, Håvard Mokleiv; Hjort, Nils Lid & Haug, Jens Kristoffer (2019). Focused Model Selection for Markov Chain Models: With an Application to Armed Conflict Data. Universitetet i Oslo.
• Cunen, Celine; Walløe, Lars & Hjort, Nils Lid (2017). Decline in energy in Antarctic minke whales during the JARPA period. Assessment via the Focused Information Criterion (FIC). IWC_SC/67A/EM04. International Whaling Commission.
• Jullum, Martin; Hjort, Nils Lid & Kolbjørnsen, Odd (2016). New focused approaches to topics within model selection and approximate Bayesian inversion. Universitetet i Oslo.

Se alle arbeider i Cristin