df.resid: residual degrees of freedom

In byandell/pda: Practial Data Analysis for Designed Experiments

Usage

df.resid(object, ...)
## Default S3 method:
df.resid(object, ...)
## S3 method for class 'lm'
df.resid(object, resid=residuals(object), ...)
## S3 method for class 'lme'
df.resid(object, resid = residuals( object ), factors, ...)
## S3 method for class 'lmer'
df.resid(object, ...)

Arguments

object	vector, list of vectors, or object from linear model fit
resid	Residuals of object
factors	Character string of factors for object
...	more vectors

Value

If a single vector is given, return its degrees of freedom corrected for the mean, length(object)-1. If a list of vectors is given (explicitly or implicitly), sum up df for each. If object is a linear model fit, extract its df.resid element or make appropriate guess based on model degrees of freedom if df.resid is missing. The lmer method attempts to find total random effects degrees of freedom.

Examples

## Not run: 
df.resid(x)df.resid(lm(y~a+b,data))

## End(Not run)

byandell/pda documentation built on May 13, 2019, 9:27 a.m.