View source: R/calculate_theta.R
calculate_theta | R Documentation |
Internal function to calculate parameters for each dimension of each hidden variable
calculate_theta( data, p_y_given_x_3d, marginal_description, smooth_marginals, dim_visible = NULL )
data |
Data provided by user |
p_y_given_x_3d |
A 3D array of numerics in range (0, 1), that represent the probability that each observed x variable belongs to n_hidden latent variables of dimension dim_hidden. p_y_given_x_3d has dimensions (n_hidden, n_samples, dim_hidden). |
marginal_description |
Character string which determines the marginal distribution of the data. single marginal description applies to all variables in biocorex |
smooth_marginals |
Boolean (TRUE/FALSE) which indicates whether Bayesian smoothing of marginal estimates should be used. |
dim_visible |
The dimension of the data provided in data - i.e. the number of discrete levels that exist in the data. Must be positive integer. |
This function is calls functions estimate_parameters_gaussian
or estimate_parameters_discrete
depending on the marginal_description
.
Returns a list of estimated parameters. The list has length = number of columns in the supplied data
. The elements of the returned list depend on the marginal_description as follows:
If the marginal description is "gaussian" a list of 2 arrays the first of which represent the estimate means, the second the estimated standard deviations. Each of these lists will have dimensions (n_hidden, dim_hidden).
If the marginal description is "discrete", each element contains a list of length...
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