Description Usage Arguments Details Value Note Author(s) References See Also Examples

This Package presents a general method for assessing the local influence of minor perturbations of case-weight for the linear regression models. The method relies on a well-behaved likelihood and certain elementary ideas from differential geometry, and seems to provide a relatively simple, unified approach for handling a variety of problems. A distinguishing feature of this method is its use of log-likelihood contours to gauge influence. Although this Package is concerned primarily with local influence, some discussion of assessing global influence, which is a significantly more difficult problem. We use geometric normal curvatures to characterize the behaviour of an influence graph around omega (Generally, omega can reflect any well-defined perturbation scheme and thus is not restricted to be a collection of case weights.),although the essential results can be obtained by using less descriptive We used it in case-Weight for the linear regression models, also recommended a general reference for deciding whether there is notable local sensitivity or not

1 | ```
LICurvature(ini = NA,X,Xstar,y,n,p, ...)
``` |

`ini` |
Initial values |

`X` |
Covariate matrix |

`Xstar` |
Design matrix |

`y` |
Continuous response |

`n` |
Design matrix |

`p` |
The number of covariates |

`...` |
Other arguments |

Models for LICurvature are specified symbolically. A typical model has the form response ~ terms where response is the (numeric) continuous response vector and terms are a series of terms which specifies a linear predictor for responses.

`lmax` |
Eign vector |

`Clmax` |
Normal curvatures for case weight in linear regression models |

Supportted by Shahid Beheshti University

Bahrami Samani and ParsaMaram

Cook, R. D. (1986). Assessment of local influence (with discussion). J. Roy. Statist. Soc. Ser. B 48: 133-169.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
data("Bahrami1")
gender<-Bahrami1$ GENDER
duration <-Bahrami1$ DURATION
y<-Bahrami1$ BMI
X=cbind(gender,duration )
Xstar=cbind(1,X)
p=2;
n=15;
ini=c(0,rep(1,p));
LICurvature(ini,X=X,Xstar=Xstar,y=y,n=n,p=p)
## The function is currently defined as
structure(function (x, ...)
UseMethod("LICurvature"), class = "LICurvature")
``` |

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