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Nonparametric regression
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<p>Nonparametric regression is a form of <a href="/facts/Regression_analysis/n6z5Tf7K">regression analysis</a> where the predictor does not take a predetermined form but is completely constructed using information derived from the data. That is, no <a href="/facts/Parametric_equation/5Uvrlgqf">parametric equation</a> is assumed for the relationship between <a href="/facts/Dependent_and_independent_variables/dINfzIF2">predictors</a> and dependent variable. A larger <a href="/facts/Sampling_(statistics)/kIb01xdL">sample</a> size is needed to build a nonparametric model having a level of <a href="/facts/Prediction_interval/0twP0IFI">uncertainty</a> as a <a href="/facts/Parametric_model/FeynAa0f">parametric model</a> because the data must supply both the model structure and the parameter estimates. </p>