GitHub

Multivariate_Newton-Raphson_method.py

y=[10.6,16.0,45.0,83.5,52.8,19.9,10.8,8.25,4.7] s=[9.34,17.9,41.5,85.5,51.5,21.5,10.8,6.29,4.14] ...
GitHub

Solving-a-coupled-ODE-using-Multivariate-Newton-Raphson-Method.

Solving a coupled ODE using Multivariate Newton Raphson Method. $\ \dfrac{dy_{1}}{dt}= -0.04y_{1} + 10^4y_{2}y_{3} $ $\ \dfrac{dy_{2}}{dt} = 0.04y_{1} - 10^4y_{2}y_{3 ...
IEEE

Newton–Raphson Meets Sparsity: Sparse Learning Via a Novel Penalty and a Fast Solver

Abstract: In machine learning and statistics, the penalized regression methods are the main tools for variable selection (or feature selection) in high-dimensional sparse data analysis. Due to the ...
Scientific Research Publishing

C. A. Lowry, W. H. Woodall, C. W. Champ and S. E. Rigdon, “A Multivariate Exponentially Weighted Moving Average Control Chart,” Technometrics, Vol. 34, No. 1, 1992, p. 46 ...

ABSTRACT: Minimax control chart uses the joint probability distribution of the maximum and minimum standardized sample means to obtain the control limits for monitoring purpose. However, the ...
IEEE

Parameter Estimation For Multivariate Generalized Gaussian Distributions

Abstract: Due to its heavy-tailed and fully parametric form, the multivariate generalized Gaussian distribution (MGGD) has been receiving much attention in signal and image processing applications.