family: Utility Functions for Error Families

Description

Utility functions for fitting Smoothing Spline ANOVA models with non-Gaussian responses.

Usage

mkdata.binomial(y, eta, wt, offset)
dev.resid.binomial(y, eta, wt)
dev.null.binomial(y, wt, offset)
cv.binomial(y, eta, wt, hat, alpha)
y0.binomial(y, eta0, wt)
proj0.binomial(y0, eta, offset)
kl.binomial(eta0, eta1, wt)
cfit.binomial(y, wt, offset)
mkdata.poisson(y, eta, wt, offset)
dev.resid.poisson(y, eta, wt)
dev.null.poisson(y, wt, offset)
cv.poisson(y, eta, wt, hat, alpha, sr, q)
y0.poisson(eta0)
proj0.poisson(y0, eta, wt, offset)
kl.poisson(eta0, eta1, wt)
cfit.poisson(y, wt, offset)
mkdata.Gamma(y, eta, wt, offset)
dev.resid.Gamma(y, eta, wt)
dev.null.Gamma(y, wt, offset)
cv.Gamma(y, eta, wt, hat, rss, alpha)
y0.Gamma(eta0)
proj0.Gamma(y0, eta, wt, offset)
kl.Gamma(eta0, eta1, wt)
cfit.Gamma(y, wt, offset)
mkdata.inverse.gaussian(y, eta, wt, offset)
dev.resid.inverse.gaussian(y, eta, wt)
dev.null.inverse.gaussian(y, wt, offset)
cv.inverse.gaussian(y, eta, wt, hat, rss, alpha)
y0.inverse.gaussian(eta0)
proj0.inverse.gaussian(y0, eta, wt, offset)
kl.inverse.gaussian(eta0, eta1, wt)
cfit.inverse.gaussian(y, wt, offset)
mkdata.nbinomial(y, eta, wt, offset, nu)
dev.resid.nbinomial(y, eta, wt)
dev.null.nbinomial(y, wt, offset)
cv.nbinomial(y, eta, wt, hat, alpha)
y0.nbinomial(y,eta0,nu)
proj0.nbinomial(y0, eta, wt, offset)
kl.nbinomial(eta0, eta1, wt, nu)
cfit.nbinomial(y, wt, offset, nu)
mkdata.polr(y, eta, wt, offset, nu)
dev.resid.polr(y, eta, wt, nu)
dev.null.polr(y, wt, offset)
cv.polr(y, eta, wt, hat, nu, alpha)
y0.polr(eta0)
proj0.polr(y0, eta, wt, offset, nu)
kl.polr(eta0, eta1, wt)
cfit.polr(y, wt, offset)
mkdata.weibull(y, eta, wt, offset, nu)
dev.resid.weibull(y, eta, wt, nu)
dev.null.weibull(y, wt, offset, nu)
cv.weibull(y, eta, wt, hat, nu, alpha)
y0.weibull(y, eta0, nu)
proj0.weibull(y0, eta, wt, offset, nu)
kl.weibull(eta0, eta1, wt, nu, int)
cfit.weibull(y, wt, offset, nu)
mkdata.lognorm(y, eta, wt, offset, nu)
dev.resid.lognorm(y, eta, wt, nu)
dev0.resid.lognorm(y, eta, wt, nu)
dev.null.lognorm(y, wt, offset, nu)
cv.lognorm(y, eta, wt, hat, nu, alpha)
y0.lognorm(y, eta0, nu)
proj0.lognorm(y0, eta, wt, offset, nu)
kl.lognorm(eta0, eta1, wt, nu, y0)
cfit.lognorm(y, wt, offset, nu)
mkdata.loglogis(y, eta, wt, offset, nu)
dev.resid.loglogis(y, eta, wt, nu)
dev0.resid.loglogis(y, eta, wt, nu)
dev.null.loglogis(y, wt, offset, nu)
cv.loglogis(y, eta, wt, hat, nu, alpha)
y0.loglogis(y, eta0, nu)
proj0.loglogis(y0, eta, wt, offset, nu)
kl.loglogis(eta0, eta1, wt, nu, y0)
cfit.loglogis(y, wt, offset, nu)

Arguments

y: Model response.
eta: Fitted values on link scale.
wt: Model weights.
offset: Model offset.
nu: Size for nbinomial. Inverse scale for log life time.