Description Usage Arguments Slots See Also

Class of object returned by the `blockSeg`

function.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
## S4 method for signature 'blockSeg'
print(x, ...)
## S4 method for signature 'blockSeg'
show(object)
getComplexity(object)
## S4 method for signature 'blockSeg'
getComplexity(object)
## S4 method for signature 'blockSeg'
residuals(object, Y)
## S4 method for signature 'blockSeg'
deviance(object, Y)
getBreaks(object)
## S4 method for signature 'blockSeg'
getBreaks(object)
getCompressYhat(object, Y)
## S4 method for signature 'blockSeg'
getCompressYhat(object, Y)
``` |

`x` |
in the print method, a blockSeg object |

`...` |
in the print method, additional parameters (ignored) |

`object` |
an object with class blockSeg |

`Y` |
the original data matrix |

`Beta`

a Matrix object of type

`dgCMatrix`

, encoding the solution path of the underlying LARS algorithm. Omitted if the`blockSeg`

function was called with the option`Beta=FALSE`

.`Lambda`

a numeric vector with the successive values of

`Lambda`

, that is, the value of the penalty parameter corresponding to a new event in the path (either a variable activation or deactivation).`RowBreaks`

a list of vectors, one per step of the LARS algorithm. Each vector contains the breaks currently identified along the ROWS of the 2-dimensional signal at the current step.

`ColBreaks`

a list of vectors, one per step of the LARS algorithm. Each vector contains the breaks currently identified along the COLUMNS of the 2-dimensional signal at the current step.

`Actions`

a list with the successive actions at each step of the LARS algorithm.

See also `plot,blockSeg-method`

, `predict,blockSeg-method`

and `blockSeg`

.

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