• Non-parametric estimation of conditional densities: A new method 

      Otneim, Håkon; Tjøstheim, Dag (Discussion paper;22/16, Working paper, 2016-12-07)
      Let X = (X1,...,Xp) be a stochastic vector having joint density function fX(x) with partitions X1 = (X1,...,Xk) and X2 = (Xk+1,...,Xp). A new method for estimating the conditional density function of X1 given X2 is presented. ...
    • Using machine learning to predict patent lawsuits 

      Juranek, Steffen; Otneim, Håkon (Discussion paper;6/21, Working paper, 2021-06-22)
      We use machine learning methods to predict which patents end up at court using the population of US patents granted between 2002 and 2005. We analyze the role of the different dimensions of an empirical analysis for the ...