RVAideMemoire (version 0.9-35)

least.rect: Least rectangles linear regression

Description

Fit a least rectangle linear regression, possibly for each level of a factor.

Usage

least.rect(formula, data, conf.level = 0.95, theo = 1)

Arguments

formula

a formula of the form y ~ x, where y and x give the y and x variable, respectively. The formula can also be y ~ x | f to fit a (separate) regression for each level of the factor f.

data

an optional data frame containing the variables in the formula formula. By default the variables are taken from environment(formula).

conf.level

confidence level.

theo

theoretical value of the slope. If several regression are fitted, the same value is used for all comparisons of slope vs. theoretical value.

Value

• coefficients
  regression parameters.
• residuals
  residuals.
• fitted.values
  fitted values.
• call
  the matched call.
• model
  the model frame used.
• conf.level
  confidence level.
• conf.int
  confidence interval of regression parameters.
• theo
  theoretical value of the slope.
• comp
  data frame of results for equality of the slope(s) to the theoretical value.
• corr
  data frame of results for significativity of the correlation coefficient(s).
• multiple
  logical, TRUE if several regressions are fitted.

Examples

x <- 1:30+rnorm(30,0,3)
y <- 1:30+rnorm(30,0,3)
regression1 <- least.rect(y~x)
summary(regression1)

x2 <- c(1:30,1:30)
y2 <- c(1:30+rnorm(30,0,3),seq(10,22,12/29)+rnorm(30,0,3))
fact <- gl(2,30,labels=LETTERS[1:2])
regression2 <- least.rect(y2~x2|fact)
summary(regression2)