Author | Lindsey, James K. author |
---|---|
Title | The Analysis of Stochastic Processes using GLIM [electronic resource] / by James K. Lindsey |
Imprint | New York, NY : Springer New York, 1992 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-2888-2 |
Descript | VI, 294 p. online resource |
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. Bloomfieldโs Exponential Model -- 5. Comparison of Spectra -- 8. Repeated Measurements -- 1. Descriptive Methods -- 2. Autoregression -- 3. Random Effects -- 4. A Generalized Linear Autoregression โModelโ -- 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