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The analysis of stochastic processes using GLIM

Author: James K Lindsey
Publisher: Berlin ; New York : Springer-Verlag, ©1992.
Series: Lecture notes in statistics (Springer-Verlag), 72.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:

The aim of this book is to present a survey of the many ways in which the statistical package GLIM may be used to model and analyze stochastic processes.

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Additional Physical Format: Online version:
Lindsey, James K.
Analysis of stochastic processes using GLIM.
Berlin ; New York : Springer-Verlag, ©1992
(OCoLC)625982032
Document Type: Book
All Authors / Contributors: James K Lindsey
ISBN: 0387977619 9780387977614 3540977619 9783540977612
OCLC Number: 26043368
Description: 294 pages ; 25 cm.
Contents: 1. Normal Theory Models and Some Extensions.- 1. Linear Regression.- 2. Analysis of Variance.- 3. Analysis of Covariance.- 4. The Extension to Non-Normal Models.- 5. Fitting Distributions.- 6. Further GLIM Instructions.- 2. Markov Chains.- 1. Binary Point Processes.- 2. Multi-state Markov Chains.- 3. Stationarity.- 4. Reversibility and Equilibrium.- 5. Random Walks.- 6. The Mover-Stayer Model.- 3. Point and Renewal Processes.- 1. Point Processes.- 2. The Poisson Process.- 3. Kaplan-Meier Estimation.- 4. Probability Plots.- 5. Fitting a Distribution.- 6. A Nonhomogeneous Point Process.- 7. An Example with Periodicity.- 4. Survival Curves.- 1. Censored Data.- 2. The Hazard Function.- 3. Exponential Distribution.- 4. Pareto Distribution.- 5. Weibull Distribution.- 6. Extreme Value Distribution.- 7. Log Normal Distribution.- 8. Log Logistic Distribution.- 9. Gamma Distribution.- 10. Inverse Gaussian Distribution.- 11. Cox Proportional Hazards Model.- 12. Piecewise Exponential Distribution.- 5. Growth Curves.- 1. Exponential Growth: Continuous Data.- 2. Exponential Growth: Count Data.- 3. The Logistic Growth Curve.- 4. The Gomperz Growth Curve.- 6. Time Series: The Time Domain.- 1. Trends and Correlograms.- 2. Autoregression and Random Walks.- 3. Examination of the Distribution Assumptions.- 4. Mis-specification of the Linear Model.- 5. Serial Correlation in Regression Analysis.- 7. Time Series: The Frequency Domain.- 1. Data Preparation: Filtering and Tapering.- 2. Periodograms.- 3. Fitting an Autoregression by Spectral Analysis.- 4. Bloomfield's Exponential Model.- 5. Comparison of Spectra.- 8. Repeated Measurements.- 1. Descriptive Methods.- 2. Autoregression.- 3. Random Effects.- 4. A Generalized Linear Autoregression "Model".- 5. A Generalized Linear Random Effects Model.- 6. A Multivariate Logistic Model.- 9. Stochastic Processes and Generalized Linear Models.- 1. A Logistic Growth Curve with Autoregression.- 2. Conditional Generalized Linear Autoregression.- 3. Exponential Dispersion Models.- 4. Two Sources of Dependence in Panel Data.- 5. Binary Crossover Trials.- 6. A Binary Model for Learning.- Appendix I - GLIM Commands.- Appendix II - GLIM Macros.- Appendix III - Data Tables.- References.
Series Title: Lecture notes in statistics (Springer-Verlag), 72.
Responsibility: James K. Lindsey.
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