hdpGLM_simParameters | R Documentation |
This function generates parameters that can be used to simulate data sets from the Hierarchical Dirichlet Process of Generalized Linear Model (hdpGLM) or dpGLM
hdpGLM_simParameters( K, nCov = 2, nCovj = 0, J = 1, pi = NULL, same.K = FALSE, seed = NULL, context.effect = NULL, same.clusters.across.contexts = NULL, context.dependent.cluster = NULL )
K |
integer, the number of clusters. If there are multiple contexts, K is the average number of clusters across contexts, and each context gets a number of clusters sampled from a Poisson distribution, except if |
nCov |
integer, the number of covariates of the GLM components |
nCovj |
an integer indicating the number of covariates determining the average parameter of the base measure of the Dirichlet process prior |
J |
an integer representing the number of contexts @param parameters either NULL or a list with the parameters to generate the model. If not NULL, it must contain a sublist name beta, a vector named tau, and a vector named pi. The sublist beta must be a list of vectors, each one with size nCov+1 to be the coefficients of the GLM mixtures components that will generate the data. For the vector tau, if nCovj=0 (single-context case) then it must be a 1x1 matrix containing 1. If ncovj>0, it must be a (nCov+1)x(nCovj+1) matrix. The vector pi must add up to 1 and have length K. |
pi |
either NULL or a vector with length K that add up to 1. If not NULL, it determines the mixture probabilities |
same.K |
boolean, used when data is sampled from more than one context. If |
seed |
a seed for |
context.effect |
either |
same.clusters.across.contexts |
boolean, if |
context.dependent.cluster |
integer, indicates which cluster will be context-dependent. If |
The function returns a list with the parameters used to generate data sets from the hdpGLM model. This list can be used in the function hdpGLM_simulateData
pars = hdpGLM_simParameters(nCov=2, K=2, nCovj=3, J=20, same.clusters.across.contexts=FALSE, context.dependent.cluster=0)
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