Nonlinear Estimation

algorithm analysis approximate asymptote binomial distribution common estimate loci computed confidence intervals confidence limits confidence regions convergence correlations corresponding critical contour curvature curve fitting data points data sets data values defining parameters deviance residuals dispersion matrix equally spaced equations error distribution example expected exponential curve fitted values function of parameters gamma distribution Gauss-Newton method given Gompertz curve initial estimates iterations likelihood contours likelihood function linear parameters linear regression log-likelihood logistic curve lognormal maximum likelihood estimates method minimum negative binomial negative binomial distribution nonlinear models nonlinear parameters normal errors normally distributed observations obtained optimization orthogonal polynomial p₁ parameter estimates parameter loci parameter space plotted Poisson distribution polynomial pseudomodels quadratic range rectangular hyperbola residual sum Royal Statistical Society sample Section solution locus solution region stable ordinates stable parameters Statistical straight line sum of squares three-parameter tion variables variance y₁ zero Φι