prml_classifier_f: PRML classifier together with density estimation of mixing...
In YunranChen/prml: An Implementation of PRML Classifier and PRML Filter

Description Usage Arguments Value See Also

PRML classifier together with density estimation of mixing density.

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prml_classifier_f(xs_bn, xs_a, xs_b, mu_l = 0, mu_u = 180, e = 0,
  r_a = 0.5, s_a = 2e-10, r_b = 0.5, s_b = 2e-10, n_gq = 20,
  n_mu = 100, 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_mu`	A number. 100 by default. The number of grids used to represent the pdf of f.
`n_per`	A number. 100 by default. Permutation of likihood estimation to obtain the order-invariant estimator.