Structured PCA

complete_log_posterior | Compute a value proportional to the expected complete log... |

compute_H | Compute all the blocks of H. |

compute_H_W | Compute all the w_i blocks of H |

cov.independent | Independant covariance function. Is zero everywhere except... |

cov.independent.d | Derivative of the independent covariance function. Does not... |

cov.MR | Noisy MR |

cov.MR.beta0 | Computationally cheap estimate for beta0 for cov.MR |

cov.MR.d | Partial derivatives of the MR |

cov.noisy.MR | Noisy MR covariance function |

cov.noisy.MR.d | Partial derivatives of the noisy MR covariance function |

cov.noisy.RQ | Noisy RQ covariance function |

cov.noisy.RQ.beta0 | Computationally cheap estimate for beta0 for cov.noisy.RQ. |

cov.noisy.RQ.d | Partial derivatives of the noisy RQ covariance function |

cov.noisy.SE | Noisy SE covariance function |

cov.noisy.SE.beta0 | Computationally cheap estimate for beta0 for cov.noisy.SE. |

cov.noisy.SE.d | Partial derivatives of the noisy SE covariance function |

cov.RQ | Rational quadratic covariance function |

cov.RQ.beta0 | Computationally cheap estimate for beta0 for cov.RQ. |

cov.RQ.d | Rational quadratic covariance function derivatives wrt... |

cov.SE | Squared exponential covariance function. |

cov.SE.beta0 | Computationally cheap estimate for beta0 for cov.SE. |

cov.SE.d | Squared exponential covariance function derivatives wrt... |

cov.taper | Taper a covariance function |

cov.taper.d | Taper a covariance function (partial derivatives) |

dlaplace | Density of the Laplace distribution |

EM.E | Expectation step |

EM.M.sigSq | Maximization step for sigma^2 |

EM.M.W | Maximization step for W |

initialize_from_ppca | Initialize mu, sigSq and W from PPCA. |

log_det_H_d | Compute the partial derivatives of log(det(H)) with respect... |

log_evidence | Compute the laplace approximation to the log evidence given... |

log_evidence_d | Compute the derivative of the approximate log evidence with... |

log_likelihood | Calculate the log likelihood for StPCA with given parameters |

log_prior | Calculate the *un-normalised* log prior (only in sigSq) for... |

log_prior_d | Compute the partial derivatives of the log prior with respect... |

log_prior_sigSq | The improper prior over sigSq. Proportional to sigma^-2 |

log_prior_W | The proper prior over W. p(W) = \prod^k_i=1 N(w_i | 0, K) |

log_sparse_prior | The *un-normalised* prior over W, sigma^2 in SpStPCA. A... |

log_sparse_prior_W | The *un-normalised* prior over W in SpStPCA. This is a... |

soft_threshold | Soft-thresholding operator. |

StpcaModel-class | Structured PCA Model |

sylSolve | Solve the sylvester equation AW + WB = C for W. |

synthesize_data | Synthesize fake data from StPCA model |

synthesize_data_kern | Synthesize fake data from StPCA model |

theta_EM | Update theta to be the maximum-a-posteriori value using... |

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