# Generate sequences using a probabilistic suffix tree

### Description

Generate sequences using a probabilistic suffix tree

### Usage

1 2 | ```
## S4 method for signature 'PSTf'
generate(object, l, n, s1, p1, method, L, cnames)
``` |

### Arguments

`object` |
a probabilistic suffix tree, i.e., an object of class |

`l` |
integer. Length of the sequence(s) to generate. |

`n` |
integer. Number of the sequence(s) to generate. |

`s1` |
character. The first state in the sequences. The length of the vector should equal |

`p1` |
numeric. An optional probability vector for generating the first position state in the sequence(s). If specified, the first state in the sequence(s) is randomly generated using the probability distribution in |

`method` |
character. If |

`L` |
integer: Maximal depth used to extract the probability distributions from the PST object. |

`cnames` |
character: Optional column (position) names for the returned state sequence object. By default, the names of the sequence object to which the model was fitted are used (slot "data" of the PST). |

### Details

As a probabilistic suffix tree (PST) represents a generating model, it can be used to generate artificial sequence data sets. Sequences are built by generating the states at each successive position. The process is similar to sequence prediction (see `predict`

), except that the retrieved conditional probability distributions provided by the PST are used to generate a symbol instead of computing the probability of an existing state. For more details, see Gabadinho 2016.

### Value

A state sequence object (an object of class `stslist`

) containing `n`

sequences. This object can be passed as argument to all the functions for visualization and analysis provided by the `TraMineR`

package.

### Author(s)

Alexis Gabadinho

### References

Gabadinho, A. & Ritschard, G. (2016). Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package. *Journal of Statistical Software*, **72**(3), pp. 1-39.

### Examples

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