loss3 function

Composite Loss Value for GLM

Compute composite loss value

loss3(y, mu, theta, weights, cfun, family, s, delta)

Arguments

• y: response variable values, 0/1 if family=2, or binomial
• mu: response prediction of y. If mu is linear predictor, use function loss2 instead
• theta: scale parameter for family=4, negative binomial
• weights: observation weights, same length as y
• cfun: integer from 1-8, concave function as in irglm_fit
• family: integer 2, 3 or 4, convex function binomial, Poisson or negative binomial, respectively
• s: tuning parameter of cfun. s > 0 and can be equal to 0 for cfun="tcave".
• delta: a small positive number provided by user only if cfun="gcave" and 0 < s <1

Returns

Weighted loss values

Details

For large s values, the loss can be 0 with cfun=2,3,4, or "acave", "bcave", "ccave".

See Also

loss2

irglm

irglmreg

loss2_irsvm

References

Zhu Wang (2024) Unified Robust Estimation, Australian & New Zealand Journal of Statistics. 66(1):77-102.

Author(s)

Zhu Wang zwang145@uthsc.edu