R: Utility Functions for Error Families

family {gss} | R Documentation

## 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.

### Note

`gssanova0` uses `mkdata.x`, `dev.resid.x`, and `dev.null.x`. `gssanova` uses the above plus `dev0.resid.x` and `cv.x`.

`y0.x`, `proj0.x`, `kl.x`, and `cfit.x` are used by `project.gssanova`.

[Package gss version 2.2-2 Index]