Generalized Least Square Method also called Least Cubic Method
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"Least Cubic Method" Also called "Generalized the Least Square Method", is new Method of data regression.
Because the sum of the deviations would, by definition, always be zero. So there is nothing to be minimised to improve the fit.
This method was governed by a variational principle applied to a certain function. The resulting variational relation was then treated by introducing some unknown multipliers in connection with constraint relations. After the elimination of these multipliers the generalized momenta were found to be certain functions of the partial derivatives of the Hamilton Jacobi function with respect to the generalized coordinates and the time. Then the partial differential equation of the classical Hamilton-Jacobi method was modified by inserting these functions for the generalized momenta in the Hamiltonian of the system.
A square prism (a cuboid with at least two square faces at its ends).
Scientists tools are are test tubes magnifying glass, beakers,and Bunsen burners.