Abstract
Consider the regression
where y t ∈ℜ 1 is the dependent variable, x t ∈ℜ q is an argument (regressor), α0∈ℜ n is a true regression parameter (unknown), \(\tilde{f}({\mathbf{x}}_{t},\alpha )\) is some (nonlinear) function of α, ε t is a noise, and t is an observation number.
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Knopov, P.S., Korkhin, A.S. (2012). Estimation of Regression Model Parameters with Specific Constraints. In: Regression Analysis Under A Priori Parameter Restrictions. Springer Optimization and Its Applications(), vol 54. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0574-0_1
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DOI: https://doi.org/10.1007/978-1-4614-0574-0_1
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