51 citations · 79 across the 8 of their papers we have counts for
8 papers
A non-parametric estimator for excess recurrent events
Jonatan Hedberg, Ola Hössjer, Caroline Nordenwall +2
Measuring disease burden is an important part of both public health research and health economics. Some measures of disease burden, such as hospitalisations, are made up of recurre…
Is it possible to know cosmological fine-tuning?
Daniel Andrés Díaz-Pachón, Ola Hössjer, Calvin Mathew
Fine-tuning studies whether some physical parameters, or relevant ratios between them, are located within so-called life-permitting intervals of small probability outside of which…
Assessing, testing and estimating the amount of fine-tuning by means of active information
Daniel Andrés Díaz-Pachón, Ola Hössjer
A general framework is introduced to estimate how much external information has been infused into a search algorithm, the so-called active information. This is rephrased as a test…
Active information, missing data and prevalence estimation
Ola Hössjer, Daniel Andrés Díaz-Pachón, Chen Zhao +1
The topic of this paper is prevalence estimation from the perspective of active information. Prevalence among tested individuals has an upward bias under the assumption that indivi…
On the Use of -functionals in Regression Models
Ola Hössjer, Måns Karlsson
In this paper we survey and unify a large class or -functionals of the conditional distribution of the response variable in regression models. This includes robust measures of l…
Sometimes size does not matter
Daniel Andrés Díaz-Pachón, Ola Hössjer, Robert J. Marks
Cosmological fine-tuning has traditionally been associated with the narrowness of the intervals in which the parameters of the physical models must be located to make life possible…
Is Cosmological Tuning Fine or Coarse?
Daniel Andrés Díaz-Pachón, Ola Hössjer, Robert J. Marks
The fine-tuning of the universe for life, the idea that the constants of nature (or ratios between them) must belong to very small intervals in order for life to exist, has been de…
A general asymptotic scheme for inference under order restrictions
D. Anevski, O. Hössjer
Limit distributions for the greatest convex minorant and its derivative are considered for a general class of stochastic processes including partial sum processes and empirical pro…