Description Usage Arguments Value Examples

Calculate the generalized membership matrix (spatial version) according to a set of centroids, the observed data, the fuzziness degree a neighbouring matrix, a spatial weighting term and a beta parameter

1 | ```
calcSFGCMBelongMatrix(centers, data, wdata, m, alpha, beta)
``` |

`centers` |
A matrix or a dataframe representing the centers of the clusters with p columns and k rows |

`data` |
A dataframe or matrix representing the observed data with n rows and p columns |

`wdata` |
A dataframe or matrix representing the lagged observed data with nrows and p columns |

`m` |
A float representing the fuzziness degree |

`alpha` |
A float representing the weight of the space in the analysis (0 is a typical fuzzy-c-mean algorithm, 1 is balanced between the two dimensions, 2 is twice the weight for space) |

`beta` |
A float for the beta parameter (control speed convergence and classification crispness) |

A n * k matrix representing the belonging probabilities of each observation to each cluster

1 | ```
#This is an internal function, no example provided
``` |

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