matrix_to_HD: Coerce matrices to hyperdirichlet objects
In hyperdirichlet: A Generalization of the Dirichlet Distribution

Description Usage Arguments Details Value Author(s) See Also Examples

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

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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, ...)

`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()`)

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).

Returns a hyperdirichlet object

Robin K. S. Hankin

mult_restricted_obs