PLNmixture_param | R Documentation |

Helper to define list of parameters to control the PLNmixture fit. All arguments have defaults.

```
PLNmixture_param(
backend = "nlopt",
trace = 1,
covariance = "spherical",
init_cl = "kmeans",
smoothing = "both",
config_optim = list(),
config_post = list(),
inception = NULL
)
```

`backend` |
optimization back used, either "nlopt" or "torch". Default is "nlopt" |

`trace` |
a integer for verbosity. |

`covariance` |
character setting the model for the covariance matrices of the mixture components. Either "full", "diagonal" or "spherical". Default is "spherical". |

`init_cl` |
The initial clustering to apply. Either, 'kmeans', CAH' or a user defined clustering given as a list of clusterings, the size of which is equal to the number of clusters considered. Default is 'kmeans'. |

`smoothing` |
The smoothing to apply. Either, 'none', forward', 'backward' or 'both'. Default is 'both'. |

`config_optim` |
a list for controlling the optimizer (either "nlopt" or "torch" backend). See details |

`config_post` |
a list for controlling the post-treatments (optional bootstrap, jackknife, R2, etc.). |

`inception` |
Set up the parameters initialization: by default, the model is initialized with a multivariate linear model applied on log-transformed data, and with the same formula as the one provided by the user. However, the user can provide a PLNfit (typically obtained from a previous fit), which sometimes speeds up the inference. |

See `PLN_param()`

for a full description of the generic optimization parameters. PLNmixture_param() also has additional parameters controlling the optimization due the inner-outer loop structure of the optimizer:

"ftol_out" outer solver stops when an optimization step changes the objective function by less than xtol multiplied by the absolute value of the parameter. Default is 1e-6

"maxit_out" outer solver stops when the number of iteration exceeds maxit_out. Default is 50

"it_smoothing" number of the iterations of the smoothing procedure. Default is 1.

list of parameters configuring the fit.

`PLN_param()`

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