R: Predicted Values Based on the Weighted BACON Linear...

predict.wbaconlm {wbacon}

R Documentation

Predicted Values Based on the Weighted BACON Linear Regression

Description

This function does exactly what predict does for the linear model lm; see predict.lm for more details.

Usage

## S3 method for class 'wbaconlm'
predict(object, newdata, se.fit = FALSE, scale = NULL,
    df = Inf, interval = c("none", "confidence", "prediction"), level = 0.95,
    type = c("response", "terms"), terms = NULL, na.action = na.pass, ...)

Arguments

`object`	Object of class inheriting from `"lm"`
`newdata`	An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
`se.fit`	A switch `[logical]` indicating if standard errors are required.
`scale`	Scale parameter for std.err. calculation, `[numeric]`.
`df`	Degrees of freedom for scale, `[integer]`.
`interval`	Type of interval calculation, `[character]`. Can be abbreviated.
`level`	Tolerance/confidence level, `[numeric]`.
`type`	Type of prediction (response or model term), `[character]`. Can be abbreviated.
`terms`	If `type = "terms"`, which terms (default is all terms), a `[character]` vector.
`na.action`	function determining what should be done with missing values in `newdata`. The default is to predict `NA`.
`...`	further arguments passed to `predict.lm`

Value

predict.wbaconlm produces a vector of predictions or a matrix of predictions and bounds with column names fit, lwr, and upr if interval is set. For type = "terms" this is a matrix with a column per term and may have an attribute "constant".

If se.fit is TRUE, a list with the following components is returned:

`fit`	vector or matrix as above
`se.fit`	standard error of predicted means
`residual.scale`	residual standard deviations
`df`	degrees of freedom for residual

Examples

data(iris)
m <- wBACON_reg(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width,
    data = iris)
predict(m, newdata = data.frame(Sepal.Width = 1, Petal.Length = 1,
    Petal.Width = 1))