1 2 3 4 5 6 7 8 9 10 11
0.2167 0.2517 0.3254 0.4542 0.2239 0.3201 0.5271 0.2819 0.3011 0.5066 0.1970
12 13 14 15 16 17 18 19 20 21 22
0.2146 0.3054 0.4397 0.2909 0.3514 0.4049 0.2448 0.3570 0.4840 0.2154 0.1835
23 24 25 26 27 28 29 30 31 32
0.2899 0.4701 0.2910 0.2982 0.5449 0.3677 0.6603 0.3181 0.2557 0.4569
Generalized Leverage Values
Description
Compute the generalized leverages values for fitted models.
Usage
gleverage(model, ...)
Arguments
model
|
a model object. |
…
|
further arguments passed to methods. |
Value
gleverage is a new generic for computing generalized leverage values as suggested by Wei, Hu, and Fung (1998). Currently, there is only a method for betareg models, implementing the formulas from Rocha and Simas (2011) which are consistent with the formulas from Ferrari and Cribari-Neto (2004) for the fixed dispersion case.
Currently, the vector of generalized leverages requires computations and storage of order \(n \times n\).
References
Ferrari SLP, Cribari-Neto F (2004). Beta Regression for Modeling Rates and Proportions. Journal of Applied Statistics, 31(7), 799–815.
Rocha AV, Simas AB (2011). Influence Diagnostics in a General Class of Beta Regression Models. Test, 20(1), 95–119. doi:10.1007/s11749-010-0189-z
Wei BC, Hu, YQ, Fung WK (1998). Generalized Leverage and Its Applications. Scandinavian Journal of Statistics, 25, 25–37.
See Also
betareg