We consider bivariate logspline density estimation for tomography data. In the usual logspline density estimation for bivariate data, the logarithm of the unknown density function is estimated by tensor product splines, the unknown parameters of which are given by maximum likelihood. In this paper we use tensor product B-splines and the projection-slice theorem to construct the logspline density estimators for tomography data. Rates of convergence are established for log-density functions assumed to belong to a Besov space.logspline models, tensor product B-splines, positron emission tomography, projection-slice theorem, Besov space, rate of convergence
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.