summary.ldbglm {dbstats} | R Documentation |

## Summarizing local distance-based generalized linear model fits

### Description

`summary`

method for class `"ldbglm"`

.

### Usage

```
## S3 method for class 'ldbglm'
summary(object,dispersion = NULL,...)
```

### Arguments

`object` |
an object of class |

`dispersion` |
the dispersion parameter for the family used.
Either a single numerical value or |

`...` |
arguments passed to or from other methods to the low level. |

### Value

A list of class `summary.ldgblm`

containing the following components:

`nobs` |
number of observations. |

`trace.hat` |
Trace of smoother matrix. |

`call` |
the matched call. |

`family` |
the |

`deviance` |
measure of discrepancy or goodness of fitt. Proportional to twice the difference between the maximum log likelihood achievable and that achieved by the model under investigation. |

`df.residual` |
the residual degrees of freedom. |

`null.deviance` |
the deviance for the null model. |

`df.null` |
the residual degrees of freedom for the null model. |

`iter` |
number of Fisher Scoring ( |

`deviance.resid` |
the deviance residuals for each observation: sign(y-mu)*sqrt(di). |

`pears.resid` |
the raw residual scaled by the estimated standard
deviation of |

`dispersion` |
the dispersion is taken as 1 for the binomial and Poisson families, and otherwise estimated by the residual Chisquared statistic (calculated from cases with non-zero weights) divided by the residual degrees of freedom. |

`kind.kernel` |
smoothing kernel function. |

`method.h` |
method used to decide the optimal bandwidth. |

`h.opt` |
the optimal bandwidth h used in the fitting proces
( |

`crit.value` |
value of criterion defined in |

### Author(s)

Boj, Eva <evaboj@ub.edu>, Caballe, Adria <adria.caballe@upc.edu>, Delicado, Pedro <pedro.delicado@upc.edu> and Fortiana, Josep <fortiana@ub.edu>

### References

Boj E, Delicado P, Fortiana J (2010). *Distance-based local linear regression for functional predictors*.
Computational Statistics and Data Analysis 54, 429-437.

Boj E, Grane A, Fortiana J, Claramunt MM (2007). *Selection of predictors in distance-based regression*.
Communications in Statistics B - Simulation and Computation 36, 87-98.

Cuadras CM, Arenas C, Fortiana J (1996). *Some computational aspects of a distance-based model
for prediction*. Communications in Statistics B - Simulation and Computation 25, 593-609.

Cuadras C, Arenas C (1990). *A distance-based regression model for prediction with mixed data*.
Communications in Statistics A - Theory and Methods 19, 2261-2279.

Cuadras CM (1989). *Distance analysis in discrimination and classification using both
continuous and categorical variables*. In: Y. Dodge (ed.), *Statistical Data Analysis and Inference*.
Amsterdam, The Netherlands: North-Holland Publishing Co., pp. 459-473.

### See Also

`ldbglm`

for local distance-based generalized linear models.

*dbstats*version 2.0.2 Index]