org.omegahat.Simulation.MCMC.Proposals
Class AdaptiveNormalProposal
java.lang.Object
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+--org.omegahat.Simulation.MCMC.Proposals.AdaptiveProposal
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+--org.omegahat.Simulation.MCMC.Proposals.AdaptiveNormalProposal
- All Implemented Interfaces:
- HastingsCoupledProposal
- public class AdaptiveNormalProposal
- extends AdaptiveProposal
Constructor Summary |
AdaptiveNormalProposal(double[] mean,
double[][] var,
double inflationFactor,
PRNG prng)
Constructor for normal with specified mean and covariance matrix. |
AdaptiveNormalProposal(double[] mean,
double[][] var,
PRNG prng)
Constructor for normal with specified mean and covariance matrix, no variance inflation |
AdaptiveNormalProposal(int length,
double mean,
double var,
double inflationFactor,
PRNG prng)
Constructor for a spherical normal with the same mean and variances for each dimension. |
AdaptiveNormalProposal(int length,
double mean,
double var,
PRNG prng)
Constructor for a spherical normal with the same mean and variances for each dimension. |
Method Summary |
void |
adapt(MultiState mstate)
modify the state of the enclosed proposal distribution using information from
the provided state vector |
(package private) double |
getInflationFactor()
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static void |
main(java.lang.String[] argv)
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(package private) double |
setInflationFactor(double in)
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Methods inherited from class java.lang.Object |
, clone, equals, finalize, getClass, hashCode, notify, notifyAll, registerNatives, toString, wait, wait, wait |
inflationFactor
protected double inflationFactor
DEBUG
protected boolean DEBUG
AdaptiveNormalProposal
public AdaptiveNormalProposal(double[] mean,
double[][] var,
PRNG prng)
- Constructor for normal with specified mean and covariance matrix, no variance inflation
- Parameters:
length
- number of dimensionsmean
- mean vectorvar
- variance matrix
AdaptiveNormalProposal
public AdaptiveNormalProposal(double[] mean,
double[][] var,
double inflationFactor,
PRNG prng)
- Constructor for normal with specified mean and covariance matrix.
- Parameters:
length
- number of dimensionsmean
- mean vectorvar
- variance matrix
AdaptiveNormalProposal
public AdaptiveNormalProposal(int length,
double mean,
double var,
PRNG prng)
- Constructor for a spherical normal with the same mean and variances for each dimension. No variance inflation.
Each element mean will be set the specified value.
The diagonal elements of the covariance matrix will be set to the specified value, with off diagonals set to 0
- Parameters:
length
- number of dimensionsmean
- mean of each dimensionvar
- diagnonal values for covariance matrix (off diagonals are set to 0)
AdaptiveNormalProposal
public AdaptiveNormalProposal(int length,
double mean,
double var,
double inflationFactor,
PRNG prng)
- Constructor for a spherical normal with the same mean and variances for each dimension.
Each element mean will be set the specified value.
The diagonal elements of the covariance matrix will be set to the specified value, with off diagonals set to 0
- Parameters:
length
- number of dimensionsmean
- mean of each dimensionvar
- diagnonal values for covariance matrix (off diagonals are set to 0)inflationFactor
- factor to inflate observed variance when adapting.
getInflationFactor
double getInflationFactor()
setInflationFactor
double setInflationFactor(double in)
adapt
public void adapt(MultiState mstate)
- Description copied from class:
AdaptiveProposal
- modify the state of the enclosed proposal distribution using information from
the provided state vector
- Overrides:
adapt
in class AdaptiveProposal
main
public static void main(java.lang.String[] argv)