DPModel_impl: Builds the source attribution model. Is not intended to be...

In sourceR: Fits a Non-Parametric Bayesian Source Attribution Model

Description

Builds the source attribution model. Is not intended to be used by a regular user. Developers only here!

Format

R6Class object.

Value

Object of R6Class.

Fields

y

3D array of [type, time, location] of the number of human cases

X

3D array of the number of positive samples for each type, source and time [type, source, time]

R

3D array of normalised relative prevalences for each timepoint [type, source, time]

Time

a character vector of timepoint ids matching time dimension in y and R

Location

a character vector of location ids matching location dimension in y

Sources

a character vector of source ids matching the source dimension in X

Type

a character vector of type ids matching the type dimension in X

prev

a 2D array (matrix) of [source, time].

a_q

concentration parameter for the DP

a_theta

shape parameter for the Gamma base distribution for the DP

b_theta

rate parameter for the Gamma base distribution for the DP

a_r

3D array of [type, src, time] for the hyperprior on the relative prevalences R

a_alpha

3D array of [source, time, location] for the prior on the alpha parameters

s

vector giving initial group allocation for each type for the DP

theta

vector giving initial values for each group in the DP

alpha

3D array of [source, time, location] giving initial values for the alpha parameters

sourceR documentation built on Aug. 31, 2020, 5:06 p.m.