(untitled) (European Journal of Pure and Applied Mathematics, 2017)
The best-known and widely used model in diffusion research is the Bass model. Estimation of its parameters has been approached in the literature by various methods, among which a very popular oneÂ is the nonlinear least squares (NLS) method proposed by Srinivasan and Mason. In this paper, we consider the l_s-norm (1≤ s<∞) generalization of the NLS method for the Bass model. Our focus is on the existence of the corresponding best l_s-norm estimate. We show that it is possible for the best l_s-norm estimate not to exist. As a main result, two theorems on the existence of the best l_s-norm estimate are obtained. One of them gives necessary and sufficient conditions which guarantee the existence of the best l_s-normÂ estimate.