`R/prml_analysis.R`

`prml_classifier.Rd`

PRML classifier: Posterior probability under each Poisson mixtures hypotheses.

prml_classifier(xs_bn, xs_a, xs_b, mu_l = "min", mu_u = "max", e = 0, r_a = 0.5, s_a = 2e-10, r_b = 0.5, s_b = 2e-10, n_gq = 20, n_per = 100)

xs_bn | A vector. Spike counts of repeated dual-stimuli trial data AB. |
---|---|

xs_a | A vector. Spike counts of repeated single-stimulus trial data A. |

xs_b | A vector. Spike counts of repeated single-stimulus trial data B. |

mu_l | A number. Lower bound of spike counts. "min" by default. Indicating \( max(0, min_{j=A,B,AB}(min(Y_j)-2{std}(Y_j))) \) |

mu_u | A number. Upper bound of spike counts. "max" by default. Indicating \( {max_{j=A,B,AB}}(max(Y_j)+2{std}(Y_j)) \) |

e | A number. 0 by default. Shringkage on the domain and meansurement of mixing density f under the Intermediate and Mixture hypothese. |

r_a | A number. The parameter in gamma prior of spike rate mu_A. rate. Jeffereys' prior by default. |

s_a | A number. The parameter in gamma prior of spike rate mu_A. shape. Jeffereys' prior by default. |

r_b | A number. The parameter in gamma prior of spike rate mu_B. rate. Jeffereys' prior by default. |

s_b | A number. The parameter in gamma prior of spike rate mu_B. shape. Jeffereys' prior by default. |

n_gq | A number. 20 by default. Number of grids in Gaussion quadrature. |

n_per | A number. 100 by default. Permutation of likihood estimation to obtain the order-invariant estimator. |

A list.

- post.prob
posterior probabilities under Mixture, Intermediate, Outside, Single hypotheses.

- win.model
the model has largest post.prob.