DirichletProcessGaussian {dirichletprocess} | R Documentation |
This is the constructor function to produce a dirichletprocess
object with a Gaussian mixture kernel with unknown mean and variance.
The base measure is a Normal Inverse Gamma distribution that is conjugate to the posterior distribution.
DirichletProcessGaussian(y, g0Priors = c(0, 1, 1, 1), alphaPriors = c(2, 4))
y |
Data |
g0Priors |
Base Distribution Priors |
alphaPriors |
Alpha prior parameters. See |
G_0(\theta | \gamma) = N \left(\mu | \mu_0, \frac{\sigma^2}{k_0} \right) \mathrm{Inv-Gamma} \left(\sigma^2 | \alpha_0, \beta_0 \right)
We recommend scaling your data to zero mean and unit variance for quicker convergence.
Dirichlet process object