residuals.ols {Design} | R Documentation

## Residuals for ols

### Description

Computes various residuals and measures of influence for a fit from `ols`.

### Usage

    ## S3 method for class 'ols':
    residuals(object,
          type=c("ordinary", "score", "dfbeta", "dfbetas",
                 "dffit", "dffits", "hat", "hscore"), ...)

### Arguments

`object` | object created by `ols`. Depending on `type`, you may have had to specify `x=TRUE` to `ols`.
`type` | type of residual desired. `"ordinary"` refers to the usual residual. `"score"` is the matrix of score residuals (contributions to first derivative of log likelihood). `dfbeta` and `dfbetas` mean respectively the raw and normalized matrix of changes in regression coefficients after deleting in turn each observation. The coefficients are normalized by their standard errors. `hat` contains the leverages — diagonals of the ``hat'' matrix. `dffit` and `dffits` contain respectively the difference and normalized difference in predicted values when each observation is omitted. The S `lm.influence` function is used. When `type="hscore"`, the ordinary residuals are divided by one minus the corresponding hat matrix diagonal element to make residuals have equal variance.
`...` | ignored

### Value

a matrix or vector, with places for observations that were originally deleted by `ols` held by `NA`s

### Author(s)

Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu

### See Also

`lm.influence`, `ols`, `which.influence`, `naresid`

### Examples

    set.seed(1)
    x1 <- rnorm(100)
    x2 <- rnorm(100)
    x1[1] <- 100
    y <- x1 + x2 + rnorm(100)
    f <- ols(y ~ x1 + x2, x=TRUE, y=TRUE)
    resid(f, "dfbetas")
    which.influence(f)

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