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This package provides algorithms that minimize the residuals between observations and model values. The least-squares optimizers minimize the distance (called cost or χ2) between model and observations.
Algorithms in this category need access to a problem (represented by a LeastSquaresProblem). Such a model predicts a set of values which the algorithm tries to match with a set of given set of observed values.
The problem can be created progressively using a builder or it can be created at once using a factory.
Since:3.3
/** * This package provides algorithms that minimize the residuals * between observations and model values. * The {@link org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer * least-squares optimizers} minimize the distance (called * <em>cost</em> or <em>&chi;<sup>2</sup></em>) between model and * observations. * * <br/> * Algorithms in this category need access to a <em>problem</em> * (represented by a {@link org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem * LeastSquaresProblem}). * Such a model predicts a set of values which the algorithm tries to match * with a set of given set of observed values. * <br/> * The problem can be created progressively using a {@link * org.apache.commons.math3.fitting.leastsquares.LeastSquaresBuilder builder} or it can * be created at once using a {@link org.apache.commons.math3.fitting.leastsquares.LeastSquaresFactory * factory}. * @since 3.3 */
package org.apache.commons.math3.fitting.leastsquares;