Description Value Author(s) See Also

An S3 class object created by `lmestCont`

function for the latent Markov (LM) model for continuous responses in long format.

`lk` |
maximum log-likelihood |

`piv` |
estimate of initial probability vector |

`Pi` |
estimate of transition probability matrices (k x k x TT) |

`Mu` |
estimate of conditional means of the response variables (r x k) |

`Si` |
estimate of var-cov matrix common to all states (r x r) |

`np` |
number of free parameters |

`k` |
optimal number of latent states |

`aic` |
value of the Akaike Information Criterion for model selection |

`bic` |
value of the Bayesian Information Criterion for model selection |

`lkv` |
log-likelihood trace at every step |

`V` |
array containing the posterior distribution of the latent states for each units and time occasion |

`n` |
number of observations in the data |

`TT` |
number of time occasions |

`modBasic` |
model on the transition probabilities: default 0 for time-heterogeneous transition matrices, 1 for time-homogeneous transition matrices, 2 for partial time homogeneity based on two transition matrices one from 2 to (TT-1) and the other for TT |

`sepiv` |
standard errors for the initial probabilities |

`sePi` |
standard errors for the transition probabilities |

`seMu` |
standard errors for the conditional means |

`seSi` |
standard errors for the var-cov matrix |

`Lk` |
vector containing the values of the log-likelihood of the LM model with each |

`Bic` |
vector containing the values of the BIC of the LM model with each |

`Aic` |
vector containing the values of the AIC of the LM model with each |

`call` |
command used to call the function |

`data` |
data frame given in input |

Francesco Bartolucci, Silvia Pandolfi, Fulvia Pennoni, Alessio Farcomeni, Alessio Serafini

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