loss3 {mpath}

Composite Loss Value for GLM

Description

Compute composite loss value

Usage

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

Details

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

Value

Weighted loss values

Author(s)

Zhu Wang <[e-mail]>

References

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

See Also

loss2 irglm irglmreg loss2_irsvm