TY - JOUR
T1 - A comparative study for the estimation of parameters in nonlinear models
AU - Kumar, Kuldeep
AU - Alsaleh, Mohammed A
PY - 1996/1/1
Y1 - 1996/1/1
N2 - The most commonly used numerical optimization techniques include the methods of Gauss-Newton, Newton-Raphson, gradient methods, including methods of steepest ascent and descent, and Marquardt algorithm. Kumar [1] has recently proposed a new technique based on optimum exponential regression. Another noniterative procedure proposed in this paper is based on the principle of internal regression. In this paper, we have compared these methods using real data sets.
AB - The most commonly used numerical optimization techniques include the methods of Gauss-Newton, Newton-Raphson, gradient methods, including methods of steepest ascent and descent, and Marquardt algorithm. Kumar [1] has recently proposed a new technique based on optimum exponential regression. Another noniterative procedure proposed in this paper is based on the principle of internal regression. In this paper, we have compared these methods using real data sets.
UR - http://www.scopus.com/inward/record.url?scp=16344391849&partnerID=8YFLogxK
U2 - 10.1016/S0096-3003(95)00211-1
DO - 10.1016/S0096-3003(95)00211-1
M3 - Article
AN - SCOPUS:16344391849
SN - 0096-3003
VL - 77
SP - 179
EP - 184
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
IS - 2-3
ER -