hyperdirichlet (version 1.5-1)

matrix_to_HD: Coerce matrices to hyperdirichlet objects

Description

Coerce matrices to hyperdirichlet objects. These functions are not intended for the user (use as.hyperdirichlet() instead).

Usage

matrix_to_HD(x, calculate_NC = FALSE, bernoulli = NULL, ...)
bernoulli_matrix_to_HD(x, calculate_NC = FALSE, ...)
multinomial_matrix_to_HD(x, calculate_NC = FALSE, ...)

Arguments

x
Matrix to be coerced
bernoulli
In function matrix_to_HD(), Boolean with TRUE meaning that the matrix rows are to be interpreted as repeated Bernoulli trials and FALSE meaning that they are interpreted as multinomial trials. Default NULL means to use a simple heuristic to infer the desired behaviour
calculate_NC
Boolean, with default FALSE meaning that the normalization constant is not to be calculated
Further arguments passed to as.hyperdirichlet() (thence to adapt())

Value

Returns a hyperdirichlet object

Details

These functions are not intended for the user; use as.hyperdirichlet() directly if at all possible.

Function bernoulli_matrix_to_HD() operates on rows. Each row has entries corresponding to the columns (the “players”). Each is a Bernoulli trial with three types of entry: NA for not playing, 1 for ‘on the winning side’ and 0 for ‘on the losing side’. Thus the Bernoulli trial is between which(x==0) and which(x==1), with the latter winning. A warning is given unless there is at least one 1 and at least one 0 on each row.

Function multinomial_matrix_to_HD() also operates on rows. Each row corresponds to a series of restricted multinomial observations with likelihood given by mult_restricted_obs() (qv).

See Also

mult_restricted_obs

Examples

Run this code
data(icons)
matrix_to_HD(icons, bern=FALSE)

Run the code above in your browser using DataLab