Package edu.cmu.tetrad.sem
Class SemEstimatorGibbs
java.lang.Object
edu.cmu.tetrad.sem.SemEstimatorGibbs
Implements the Gibbs sampler apporach to obtain samples of arbitrary size
 from the posterior distribution over the freeParameters of a SEM given a
 continuous dataset and a SemPm. Point estimates, standard deviations and
 interval estimates for the freeParameters can be computed from these samples. See
 "Bayesian Estimation and Testing of Structural Equation Models" by Scheines,
 Hoijtink and Boomsma, Psychometrika, v. 64, no. 1.
- Author:
- Frank Wimberly
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Constructor SummaryConstructorsConstructorDescriptionSemEstimatorGibbs(int numIterations, double stretch1, double stretch2, double tolerance, double priorVariance, SemPm semPm, SemIm startIm, boolean flatPrior) SemEstimatorGibbs(SemPm semPm, SemIm startIm, double[][] sampleCovars, boolean flatPrior, double stretch, int numIterations) 
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Method Summary
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Constructor Details- 
SemEstimatorGibbspublic SemEstimatorGibbs(SemPm semPm, SemIm startIm, double[][] sampleCovars, boolean flatPrior, double stretch, int numIterations) - Parameters:
- semPm- a SemPm specifying the graph and parameterization for the model.
- startIm- SemIm
- sampleCovars- sample covariance matrix
- flatPrior- whether or not the prior is informative
- stretch- scaling for the variance
- numIterations- number of times to iterate sampler
 
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SemEstimatorGibbs
 
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Method Details