Background and activities
Bo Henry Lindqvist is professor in statistics at the Department of Mathematical Sciences.
- Theoretical statistics
- Applied probability
- Reliability and survival analysis
- Cand.real 1975 (University of Oslo)
- Dr.Philos. 1982 (University of Oslo)
- Professor in statistics, Dep of Math. Sci., NTNU 1988 –
- Associate professor, Dep of Math. Statist., NTH 1979 – 88
- Research fellow, Dep. of Math., Univ. of Oslo 1978 – 79
- Assistant professor, Dep. of Math.,Univ. of Oslo 1976 – 78
- Research assistant, Dep. of Math., Univ. of Oslo 1974 – 75
- The American Statistical Association (fellow)
- The Royal Norwegian Society of Sciences and Letters (elected)
- International Statistical Institute (elected)
- Bernoulli Society for Mathematical Statistics and Probability
- The International Society for Business and Industrial Statistics
- European Network for Business and Industrial Statistics
- The Norwegian Statistical Society
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
- (2019) MACPET: model-based analysis for ChIA-PET. Biostatistics.
- (2019) End of performance prediction of lithium-ion batteries. Journal of QualityTechnology. vol. 51 (2).
- (2018) Conditional fiducial models. Journal of Statistical Planning and Inference. vol. 195.
- (2017) On the proper treatment of improper distributions. Journal of Statistical Planning and Inference. vol. 195.
- (2017) Modeling of semi-competing risks by means of first passage times of a stochastic process. Lifetime Data Analysis. vol. 24 (1).
- (2017) Nonhomogeneous Poisson process with nonparametric frailty and covariates. Reliability Engineering & System Safety. vol. 167.
- (2016) Nonparametric estimation in trend-renewal processes. Reliability Engineering & System Safety. vol. 145.
- (2016) On the equivalence of systems of different sizes, with applications to system comparisons. Advances in Applied Probability. vol. 48 (2).
- (2016) Reliability of wind turbines modeled by a Poisson process with covariates, unobserved heterogeneity and seasonality. Wind Energy. vol. 19 (11).
- (2015) Extending minimal repair models for repairable systems: A comparison of dynamic and heterogeneous extensions of a nonhomogeneous Poisson process. Reliability Engineering & System Safety. vol. 140.
- (2015) Residual plots to reveal the functional form for covariates in parametric accelerated failure time models. Lifetime Data Analysis. vol. 21 (3).
- (2015) On the signature of a system under minimal repair. Applied Stochastic Models in Business and Industry. vol. 31 (3).
- (2014) Competing risks. Lifetime Data Analysis. vol. 20 (2).
- (2013) Fiducial theory and optimal inference. Annals of Statistics. vol. 41 (1).
- (2010) Improper Priors Are Not Improper. American Statistician. vol. 64 (2).
- (2008) Breast cancer tumor growth estimated through mammography screening data. Breast Cancer Research. vol. 10 (3).
- (2006) On the statistical modeling and analysis of repairable systems. Statistical Science. vol. 21 (4).
- (2005) Estimating the proportion of true null hypotheses, with application to DNA microarray data. Journal of The Royal Statistical Society Series B-statistical Methodology. vol. 67.
- (2005) Monte Carlo conditioning on a sufficient statistic. Biometrika. vol. 92.
- (2004) The Identifiability Problem for Repairable Systems Subject to Competing Risks. Advances in Applied Probability. vol. 36.
- (2003) Estimation and Inference in Nonparametric Cox-models: Time Transformation Methods. Computational statistics (Zeitschrift). vol. 18.
- (2003) The trend-renewal process for statistical analysis of repairable systems. Technometrics. vol. 45.
- (1998) TTT-based tests for trend in repairable systems data. Reliability Engineering & System Safety. vol. 60 (1).
- (2011) Applied Nonparametric Statistics in Reliability. Springer Science+Business Media B.V.. 2011. ISBN 978-0-85729-117-2. Springer Series in Reliability Engineering (-).
Part of book/report
- (2018) Phase-Type Models and Their Extension to Competing Risks. Recent Advances in Multi-state Systems Reliability: Theory and Applications.