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Nonlinear Regression- It specifies the dependent variable being a function with a set of nonlinear parameters and a number of variables that match to the data. y=f(X,β) + ε Nonlinear regression can be used to fit nonlinear functions or intricate styles to the data, generate predictions and review parameter self-assurance intervals. Time Series Analysis- It really is a way that specials with time-based mostly info.
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y=β0 + ∑ βiXi + εi where, β signifies linear parameter, and ε signifies the error conditions There are many linear regression analyses product accessible.
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