SAS files
Chapter 5 – Regression Computations
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Checks Example 5.1, showing the condition of a simple regression problem for changes in the response variable. |
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Checks Example 5.2, showing the condition of a simple regression problem for changes in the explanatory variable. |
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Computes regression statistics for example from Brownlee, p 463, Example 13.1, which is used in demonstrations flyreg and sweep. Uses data in file brown463.dat. |
Chapter 9 – Maximum Likelihood and Nonlinear Regression
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Computes results from simple nonlinear regression Example 9.6 (Bates & Watts, BOD 1) to be compared with demonstration conclk. |
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Computes results for logistic regression in Example 9.7 (Cox) to be compared with results in the demonstration chex97. |
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Computes results for logistic regression in Example 9.8 (Finney) to be compared with results in the demonstration chex98. Uses file finney.dat. |
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Computes results for Poisson regression in Example 9.9 (Frome) to be compared with results in the demonstration chex99. Uses file frome.dat. |
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Computes results from polynomial regression test problem (Exercise 5.5) to be compared with results from demonstration nllsqt0. |
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Computes results from nonlinear regression on first test problem (Fuller) to be compared with the results from demonstration nllsqt1. Uses file fulnls.dat. |
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Computes results from nonlinear regression on second test problem (Gallant) to be compared with the results from demonstration nllsqt2. Uses file gallant.dat. |
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Mimics the computations in the demonstration chex131 (MCMC on variance components problem, Example 13.1), but does not reproduce the same output as the Fortran code since SAS uses different algorithms for generating normal and gamma variates. |
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Mimics the computations in the demonstration chex133 (Metropolis within Gibbs on Pump Example 13.3), but does not reproduce the same output as the Fortran code since SAS uses different algorithms for generating gamma variates. |
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Reproduces results from demonstration mh1 (Metropolis-Hastings on log-series posterior, Example 13.5 ), including means, autocorrelation, as well as batching and spectral density variance estimates. |
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Reproduces results from demonstration mh2 (Metropolis-Hastings on log-series posterior, Example 13.5), including means, variances and spectral density variance estimates for doing the Geweke test. |
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Reproduces results from demonstration mh3 (Metropolis-Hastings on log-series posterior, Example 13.5), including batch means and spectral density estimates, and Gelman-Rubin test results. |