Nonlinear least squares Sample Clauses

Nonlinear least squares.  To obtain parameter estimates in Models (2.8) or (2.9), one approach is to use non- linear least squares, i.e., minimizing Σ Yi −  φ1 φ3 (x −φ ) or 2 Σ  1+exp(−λ)  1 + exp − i 2 1 + exp − i φ3 Xx − (x −φ )  . Even though Xx is binary in our models and is not normally distributed, the nonlinear least-squares estimates are consistent as long as Models (1) and (2) are correctly specified. Estimation by nonlinear least squares is attractive as it can be performed by either the nls or nlme functions in R, which can incorporate survey weights or random effects.
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