Author | Ross, Gavin J. S. author |
---|---|
Title | Nonlinear Estimation [electronic resource] / by Gavin J. S. Ross |
Imprint | New York, NY : Springer New York, 1990 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-3412-8 |
Descript | VIII, 189 p. online resource |
1 Models, Parameters, and Estimation -- 1.1. The Models To Be Considered -- 1.2. Maximum Likelihood Estimation -- 2 Transformations of Parameters -- 2.1. What Are Parameters? -- 2.2. A Priori Stable Parameters -- 2.3. A Posteriori Stable Parameters -- 2.4. Theoretical Justification for Stable Parameters Using Deviance Residuals -- 2.5. Similarity of Models -- 3 Inference and Stable Transformations -- 3.1. Existence and Uniqueness of Solutions -- 3.2. Inferences on Functions of Parameters -- 3.3. Effective Replication, Influential Observations, and Design -- 4 The Geometry of Nonlinear Inference -- 4.1. The Role of Graphical Representations -- 4.2. Data Plots in (x?y)Space -- 4.3. Data Plots in (y?y)Space -- 4.4. Plots in Parameter Space -- 5 Computing Methods for Nonlinear Modeling -- 5.1. Computer Programs, Libraries, and Packages -- 5.2. Requirements for Fitting Nonlinear Models -- 5.3. Algorithms for Nonlinear Inference -- 5.4. Separable Linear Parameters -- 5.5. Confidence Intervals for Parameters and Functions -- 6 Practical Applications of Nonlinear Modeling -- 6.1. Some Questions To Be Asked in any Practical Application -- 6.2 Curve Fitting to Regular Observations in Time -- 6.3. Fitting Data to Models Defined by Differential Equations -- 7 A Program for Fitting Nonlinear Models, MLP -- 7.1. Structure of MLP -- 7.2. Curve Fitting y = f(x, ?)+ ? -- 7.3. Fitting Frequency Distributions -- 7.4. Standard Biological Models Requiring Maximum Likelihood Estimation -- 7.5. General User-Defined Models in MLP -- Appendix Glossary of Unfamiliar Terms Used in This Work -- References -- Author Index