clusterAlgoPredict {MixAll} | R Documentation |
ClusterAlgoPredict
] classA prediction algorithm is a two stage algorithm. In the first stage we perform a Monte Carlo algorithm for simulating both missing values and latent class variables. In the second stage, we simulate or impute missing values.
clusterAlgoPredict(algo = "EM", nbIterBurn = 50, nbIterLong = 100, epsilon = 1e-07)
algo |
character string with the second stage estimation algorithm. Possible values are "EM", "SemiSEM". Default value is "EM". |
nbIterBurn |
Integer defining the maximal number of burning iterations. Default value is 50. |
nbIterLong |
Integer defining the maximal number of iterations. Default value is 100. |
epsilon |
Real defining the epsilon value for the algorithm. Not used with "semiSEM" algorithms. Default value is 1.e-7. |
The epsilon value is not used when the algorithm is "SemiSEM".
a [ClusterAlgoPredict
] object
Serge Iovleff
clusterAlgoPredict() clusterAlgoPredict(algo="SemiSEM", nbIterBurn=0) clusterAlgoPredict(algo="EM", epsilon = 1e-06)