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Fast maximum likelihood estimation for general hierarchical models. [PDF]
J Appl StatHong J, Stoudt S, de Valpine P.
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A tight fit of the SIR dynamic epidemic model to daily cases of COVID-19 reported during the 2021-2022 Omicron surge in New York City: A novel approach. [PDF]
Stat Methods Med ResHarris JE.
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Plane stress finite element modelling of arbitrary compressible hyperelastic materials. [PDF]
Acta MechAhmadi M +3 more
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Fault diagnosis of permanent magnet synchronous motor based on MTF fusion image and NRBO-SCN method. [PDF]
Sci RepYu Y +5 more
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Applied Numerical Mathematics, 1990
Let g: \(R^ 1\to R^ 1\) be a differentiable function. For the numerical solutions of the equation \(g(x)=0\) a randomized Newton process of the form \(X_{k+1}=x_ k-(g(x_ k)+Z_{1,k})/(g'(x_ k)+Z_{2,k}),\quad k=0,1,...,\) is considered where \(Z_{1,k}\), \(Z_{2,k}\) are mutually independent random variables with controllable densities and hence \(\{X_ k\}
Joseph, G., Levine, A., Liukkonen, J.
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Let g: \(R^ 1\to R^ 1\) be a differentiable function. For the numerical solutions of the equation \(g(x)=0\) a randomized Newton process of the form \(X_{k+1}=x_ k-(g(x_ k)+Z_{1,k})/(g'(x_ k)+Z_{2,k}),\quad k=0,1,...,\) is considered where \(Z_{1,k}\), \(Z_{2,k}\) are mutually independent random variables with controllable densities and hence \(\{X_ k\}
Joseph, G., Levine, A., Liukkonen, J.
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Improvements of the Newton–Raphson method
Journal of Computational and Applied Mathematics, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A modified Newton–Raphson method
Communications in Numerical Methods in Engineering, 2004AbstractIn this paper, we propose the following modified Newton–Raphson iteration formulation: In case r=1, the obtained formulation reduces to the Newton–Raphson formulation. The present technique circumvent pitfalls of the Newton–Raphson iteration method. Some examples are illustrated. Copyright © 2004 John Wiley & Sons, Ltd.
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