Multivariate interpolation of scattered data by moving least squares methods
Algorithms for approximation
Nonlinear Lp-norm estimation
Mathematical algorithms for linear regression
Mathematical algorithms for linear regression
Adapted wavelet analysis from theory to software
Adapted wavelet analysis from theory to software
Applied Mathematics and Computation
The existence of optimal parameters of the generalized logistic function
Applied Mathematics and Computation
Analysis of a parameter identification problem
Applied Mathematics and Computation
Discrete total lp-norm approximation problem for the exponential function
Applied Mathematics and Computation
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Total least squares fitting Bass diffusion model
Mathematical and Computer Modelling: An International Journal
Journal of Computational and Applied Mathematics
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In this paper we propose a new method for the parameter identification in new product diffusion models. The method can be used regardless of whether the analytical solution of the differential equation describing the model is known or not. This is the main advantage of our method over the known methods. Another advantage of this method is the simplicity of its implementation and negligible computing time. The method is based on finite differences method and the moving least squares method for data smoothing.