Bootstrap sampler that is specialized to allow for the bootstrapping of RealMatrix.
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typedef Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > | MatType |
| Convenience definition.
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| BootstrapSampler (const MatType &orig_data, size_t block_size=1) |
| Constructor for the sampler.
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virtual | ~BootstrapSampler () |
| Destructor.
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virtual void | operator() (size_t num_samp, MatType &bootstrapped_sample) |
| Generate and store a new bootstrapped sample into bootstrapped_sample.
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| BootstrapSamplerBase (size_t data_size, Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > orig_data) |
| Constructor for the bootstrap functor base.
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virtual | ~BootstrapSamplerBase () |
| Destructor.
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virtual void | operator() (Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > &bootstrapped_sample) |
| Generate and store an dataSize out of dataSize bootstrap sample.
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virtual Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > | operator() () |
| Return bootstrapped sample.
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virtual size_t | getDataSize () |
| Obatin the number of samples used in the empirical distribution.
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size_t | blockSize |
| Size of the block defining a sample.
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boost::random::uniform_int_distribution | sampler |
| Uniform distribution to provide samples from the empirical distribution.
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const size_t | dataSize |
| Size of the dataset defining the empirical distribution.
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Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > | origData |
| Original data defining the empirical distribution TODO: Consider if it should be const (breaks Teuchos)
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static void | set_seed (size_t seed) |
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static boost::random::mt19937 | bootstrapRNG |
| Random number generator to use for sampling. More...
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template<typename OrdinalType, typename ScalarType>
class Dakota::BootstrapSampler< Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > >
Bootstrap sampler that is specialized to allow for the bootstrapping of RealMatrix.
The documentation for this class was generated from the following file: