Amazon cover image
Image from Amazon.com

Growth curve modeling : theory and applications / Michael J. Panik, Department of Economics, University of Hartford, West Hartford, Connecticut.

By: Material type: TextTextPublisher: Hoboken, New Jersey : John Wiley & Sons, Inc., [2014]Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118763940
  • 1118763947
  • 9781118763902
  • 1118763904
  • 9781118763971
  • 1118763971
  • 1118764048
  • 9781118764046
Subject(s): Genre/Form: Additional physical formats: Print version:: Growth curve modeling.DDC classification:
  • 519.5 23
LOC classification:
  • QA276
Online resources:
Contents:
Title page; copyright; dedication; preface; 1 mathematical preliminaries; 1.1 arithmetic progression; 1.2 geometric progression; 1.3 the binomial formula; 1.4 the calculus of finite differences; 1.5 the number e; 1.6 the natural logarithm; 1.7 the exponential function; 1.8 exponential and logarithmic functions: another look; 1.9 change of base of a logarithm; 1.10 the arithmetic (natural) scale versus the logarithmic scale; 1.11 compound interest arithmetic; 2 fundamentals of growth; 2.1 time series data; 2.2 relative and average rates of change; 2.3 annual rates of change.
2.4 discrete versus continuous growth2.5 the growth of a variable expressed in terms of the growth of its individual arguments; 2.6 growth rate variability; 2.7 growth in a mixture of variables; 3 parametric growth curve modeling; 3.1 introduction; 3.2 the linear growth model; 3.3 the logarithmic reciprocal model; 3.4 the logistic model; 3.5 the gompertz model; 3.6 the weibull model; 3.7 the negative exponential model; 3.8 the von bertalanffy model; 3.9 the log-logistic model; 3.10 the brody growth model; 3.11 the janoschek growth model; 3.12 the lundqvist-korf growth model.
3.13 the hossfeld growth model3.14 the stannard growth model; 3.15 the schnute growth model; 3.16 the morgan-mercer-flodin (m-m-f) growth model; 3.17 the mcdill-amateis growth model; 3.18 an assortment of additional growth models; appendix 3.a the logistic model derived; appendix 3.b the gompertz model derived; appendix 3.c the negative exponential model derived; appendix 3.d the von bertalanffy and richards models derived; appendix 3.e the schnute model derived; appendix 3.f the mcdill-amateis model derived; appendix 3.g the sloboda model derived.
Appendix 3.h a generalized michaelis-menten growth equation4 estimation of trend; 4.1 linear trend equation; 4.2 ordinary least squares (ols) estimation; 4.3 maximum likelihood (ml) estimation; 4.4 the sas system; 4.5 changing the unit of time; 4.6 autocorrelated errors; 4.7 polynomial models in t; 4.8 issues involving trended data; appendix 4.a ols estimated and related growth rates; 5 dynamic site equations obtained from growth models; 5.1 introduction; 5.2 base-age-specific (bas) models; 5.3 algebraic difference approach (ada) models.
5.4 generalized algebraic difference approach (gada) models5.5 a site equation generating function; 5.6 the grounded gada (g-gada) model; appendix 5.a glossary of selected forestry terms; 6 nonlinear regression; 6.1 intrinsic linearity/nonlinearity; 6.2 estimation of intrinsically nonlinear regression models; appendix 6.a gauss-newton iteration scheme: the single parameter case; appendix 6.b gauss-newton iteration scheme: the r parameter case; appendix 6.c the newton-raphson and scoring methods; appendix 6.d the levenberg-marquardt modification/compromise.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

Includes bibliographical references and index.

Print version record and CIP data provided by publisher.

Title page; copyright; dedication; preface; 1 mathematical preliminaries; 1.1 arithmetic progression; 1.2 geometric progression; 1.3 the binomial formula; 1.4 the calculus of finite differences; 1.5 the number e; 1.6 the natural logarithm; 1.7 the exponential function; 1.8 exponential and logarithmic functions: another look; 1.9 change of base of a logarithm; 1.10 the arithmetic (natural) scale versus the logarithmic scale; 1.11 compound interest arithmetic; 2 fundamentals of growth; 2.1 time series data; 2.2 relative and average rates of change; 2.3 annual rates of change.

2.4 discrete versus continuous growth2.5 the growth of a variable expressed in terms of the growth of its individual arguments; 2.6 growth rate variability; 2.7 growth in a mixture of variables; 3 parametric growth curve modeling; 3.1 introduction; 3.2 the linear growth model; 3.3 the logarithmic reciprocal model; 3.4 the logistic model; 3.5 the gompertz model; 3.6 the weibull model; 3.7 the negative exponential model; 3.8 the von bertalanffy model; 3.9 the log-logistic model; 3.10 the brody growth model; 3.11 the janoschek growth model; 3.12 the lundqvist-korf growth model.

3.13 the hossfeld growth model3.14 the stannard growth model; 3.15 the schnute growth model; 3.16 the morgan-mercer-flodin (m-m-f) growth model; 3.17 the mcdill-amateis growth model; 3.18 an assortment of additional growth models; appendix 3.a the logistic model derived; appendix 3.b the gompertz model derived; appendix 3.c the negative exponential model derived; appendix 3.d the von bertalanffy and richards models derived; appendix 3.e the schnute model derived; appendix 3.f the mcdill-amateis model derived; appendix 3.g the sloboda model derived.

Appendix 3.h a generalized michaelis-menten growth equation4 estimation of trend; 4.1 linear trend equation; 4.2 ordinary least squares (ols) estimation; 4.3 maximum likelihood (ml) estimation; 4.4 the sas system; 4.5 changing the unit of time; 4.6 autocorrelated errors; 4.7 polynomial models in t; 4.8 issues involving trended data; appendix 4.a ols estimated and related growth rates; 5 dynamic site equations obtained from growth models; 5.1 introduction; 5.2 base-age-specific (bas) models; 5.3 algebraic difference approach (ada) models.

5.4 generalized algebraic difference approach (gada) models5.5 a site equation generating function; 5.6 the grounded gada (g-gada) model; appendix 5.a glossary of selected forestry terms; 6 nonlinear regression; 6.1 intrinsic linearity/nonlinearity; 6.2 estimation of intrinsically nonlinear regression models; appendix 6.a gauss-newton iteration scheme: the single parameter case; appendix 6.b gauss-newton iteration scheme: the r parameter case; appendix 6.c the newton-raphson and scoring methods; appendix 6.d the levenberg-marquardt modification/compromise.