cytopt_minmax_r {CytOpT} | R Documentation |

## Function to estimate the type cell proportions in an unclassified cytometry data set denoted X_s by using the classification Lab_source from an other cytometry data set X_s. With this function an additional regularization parameter on the class proportions enables a faster computation of the estimator.

### Description

Function to estimate the type cell proportions in an unclassified cytometry data set denoted X_s by using the classification Lab_source from an other cytometry data set X_s. With this function an additional regularization parameter on the class proportions enables a faster computation of the estimator.

### Usage

```
cytopt_minmax_r(
X_s,
X_t,
Lab_source,
theta_true = NULL,
eps = 1e-04,
lbd = 1e-04,
n_iter = 10000,
step = 5,
power = 0.99,
monitoring = FALSE
)
```

### Arguments

`X_s` |
Cytometry data set. The columns correspond to the different biological markers tracked. One line corresponds to the cytometry measurements performed on one cell. The classification of this Cytometry data set must be provided with the Lab_source parameters. |

`X_t` |
Cytometry data set. The columns correspond to the different biological markers tracked. One line corresponds to the cytometry measurements performed on one cell. The CytOpT algorithm targets the cell type proportion in this Cytometry data set. |

`Lab_source` |
Classification of the X_s Cytometry data set |

`theta_true` |
If available, gold-standard proportions in the target data
set |

`eps` |
Regularization parameter of the Wasserstein distance |

`lbd` |
an float constant that multiply the step-size policy. Default is |

`n_iter` |
an integer Constant that iterate method select. Default is |

`step` |
Constant that multiply the step-size policy. Default is |

`power` |
the step size policy of the gradient ascent method is step/n^power.
Default is |

`monitoring` |
boolean indicating whether Kullback-Leibler divergence should be
monitored and store throughout the optimization iterations. Default is |

### Value

A list with the following elements:`Results_Minmax`

*CytOpT*version 0.9.4 Index]