Estimate Kernelized Stein Discrepancy (KSD)

Calculates the likelihood for a given dataset for a GMM

1 | ```
likelihoodgmm(model = NULL, X = NULL)
``` |

`model` |
: The Gaussian Mixture Model |

`X` |
(n by d): The dataset of interest, where n is the number of samples and d is the dimension |

P (n by k) : The likelihood of each dataset belonging to each of the k component

1 2 3 4 5 | ```
# compute likelihood for a default 1-d gaussian mixture model
# and dataset generated from it
model <- gmm()
X <- rgmm(model)
p <- likelihoodgmm(model=model, X=X)
``` |

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