Terramodel least squares
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The method of least squares grew out of the fields of astronomy and geodesy, as scientists and mathematicians sought to provide solutions to the challenges of navigating the Earth's oceans during the Age of Exploration.
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The best fit in the least-squares sense minimizes the sum of squared residuals (a residual being: the difference between an observed value, and the fitted value provided by a model). The most important application is in data fitting. The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems (sets of equations in which there are more equations than unknowns) by minimizing the sum of the squares of the residuals made in the results of every single equation.
#Terramodel least squares series#
Part of a series onĬonic fitting a set of points using least-squares approximation It is not to be confused with Least-squares function approximation. "Least squares approximation" redirects here.