Blar i NHH Brage på forfatter "Tjøstheim, Dag"

Viser treff 1-5 av 5

    • A convolution estimator for the density of nonlinear regression observations 

      Støve, Bård; Tjøstheim, Dag (Discussion paper, Working paper, 2007-11)
      The problem of estimating an unknown density function has been widely studied. In this paper we present a convolution estimator for the density of the responses in a nonlinear regression model. The rate of convergence for ...

    • Measuring asymmetries in financial returns : an empirical investigation using local gaussian correlation 

      Støve, Bård; Tjøstheim, Dag (Working paper;12/13, Working paper, 2013-03)
      A number of studies have provided evidence that financial returns exhibit asymmetric dependence, such as increased dependence during bear markets, but there seems to be no agreement as to how such asymmetries should be ...

    • Measuring financial contagion by local Gaussian correlation 

      Støve, Bård; Tjøstheim, Dag; Hufthammer, Karl Ove (Discussion paper, Working paper, 2010-09)
      This paper examines financial contagion, that is, whether the cross-market linkages in financial markets increases after a shock to a country. We introduce the use of a new measure of local dependence (introduced by ...

    • 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. ...

    • Recognizing and visualizing copulas : an approach using local Gaussian approximation 

      Berentsen, Geir Drage; Støve, Bård; Tjøstheim, Dag; Nordbø, Tommy (Working paper;12/12, Working paper, 2012-06)
      Copulas are much used to model nonlinear and non-Gaussian dependence between stochastic variables. Their functional form is determined by a few parameters, but unlike a dependence measure like the correlation, these ...