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Nonlinear Regression Modeling
David A. Ratkowsky
其他書名
A Unified Practical Approach
出版M. Dekker, 1983
主題Mathematics / Probability & Statistics / Regression Analysis
ISBN08247190779780824719074
URLhttp://books.google.com.hk/books?id=OAd_OMvm6N0C&hl=&source=gbs_api
註釋Introduction to regression models; Linear regression models; Nonlinear regression models; Geometrical representation of nonlinear regression models; The concept of nonlinear estimation behavior of nonlinear regression models; Assessing nonlinearity in nonlinear regression models; Obtaining the LS estimates of the parameters; Goodness of fit of a model; The curvature measures of nonlinearity of bates and watts; The bias calculation of M.J. Box; Simulation studies; Confidence regions for the parameters; t-Values for the parameter estimates; Asymmetry measure of bias; Some remarks on reparameterizations; Examination of nonlinearity in the yield-density models; Choice of yield-density model; Sigmoidal growth models; Stability of parameter estimates to varying assumptions about the error term; Examination of nonlinearity in the sigmoidal growth models; Searching for better parameterizations of the growth models; Choice of growth model or model function; Interpretation of the parameters in the sigmoidal growth models; Asymptotic regression model; Examination of nonlinearity in the asymptotic regression model; Positioning the design values X; Choice of model function for the asymptotic regression model; Some miscellaneous models; Model relating the age of wild rabbits to the weight of their eye lenses; Model describing catalytic chemical reaction; Model and data set from a paper of meyer and roth (1972); Model relating the resistance of a thermistor to temperature; Bent-hyperbola regression models; Comparing parameter estimates from more than one data set; Comparing parameter estimates in linear models; Comparing parameter estimates in nonlinear models; Discussion of comparison of parameters procedures; Obtaining good initial parameter estimates; Initial parameter estimates for yield-density models; Holliday model; Farazdaghi-Harris model; Bleasdale-nelder model; Initial parameter estimates for sigmoidal growth models; Gompertz model; Logistic model; Richards model; Morgan-mercel-flodin (MMF) model; Weibull-type model; Initial parameter estimates for the asymptotic regression model; Summary: toward a unified approach to nonlinear regression modeling; Consequences of intrinsic nonlinearity; Consequences of parameter-effects nonlinearity; Some fallacies in nonlinear regression modeling; Recommendations to the modeller on the procedure for examining nonlinear behavior.