prml_tests_f: PRML filter and PRML classifier together with density...
In YunranChen/prml: An Implementation of PRML Classifier and PRML Filter

Description Usage Arguments Value See Also

PRML filter and PRML classifier together with density estimation of mixing density.

prml_tests_f(xA, xB, xAB, labels = c("A", "B", "AB"),
  remove.zeros = FALSE, mu_l = "min", mu_u = "max", e = 0,
  gamma.pars = c(0.5, 2e-10), n_gq = 20, n_mu = 100, n_per = 100,
  alpha = 0.5)

`xA`	A vector. Spike counts of repeated dual-stimuli trial data AB.
`xB`	A vector. Spike counts of repeated single-stimulus trial data A.
`xAB`	A vector. Spike counts of repeated single-stimulus trial data B.
`labels`	A vector. labels for the trials.
`remove.zeros`	A logical value. Whether to remove 0s in spike counts.
`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.
`gamma.pars`	A length 2 vector. The shape and rate of gamma prior for spike rate mu_A and mu_B. 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.
`alpha`	0.5 by default. (For PRML filter) The range of the spike counts estimator [Y_{0.25}-α {IQR},Y_{0.75}+α {IQR}]