regtol.int {tolerance} | R Documentation |
Provides 1-sided or 2-sided (multiple) linear regression tolerance bounds. It is also possible to fit a regression through the origin model.
regtol.int(reg, new.x = NULL, side = 1, alpha = 0.05, P = 0.99)
reg |
An object of class lm (i.e., the results from a linear regression routine). |
new.x |
Any new levels of the predictor(s) for which to report the tolerance bounds. The number of columns must equal
the number of predictors appearing on the right-hand side of the model in reg . |
side |
Whether a 1-sided or 2-sided tolerance bound is required (determined by side = 1 or side = 2 ,
respectively). |
alpha |
The level chosen such that 1-alpha is the confidence level. |
P |
The proportion of the population to be covered by the tolerance bound(s). |
regtol.int
returns a data frame with items:
alpha |
The specified significance level. |
P |
The proportion of the population covered by the tolerance bound(s). |
y |
The value of the response given on the left-hand side of the model in reg . |
y.hat |
The predicted value of the response for the fitted linear regression model. This data frame is sorted by this value. |
1-sided.lower |
The 1-sided lower tolerance bound. This is given only if side = 1 . |
1-sided.upper |
The 1-sided upper tolerance bound. This is given only if side = 1 . |
2-sided.lower |
The 2-sided lower tolerance bound. This is given only if side = 2 . |
2-sided.upper |
The 2-sided upper tolerance bound. This is given only if side = 2 . |
Wallis, W. A. (1951), Tolerance Intervals for Linear Regression, in Second Berkeley Symposium on Mathematical Statistics and Probability, ed. J. Neyman, Berkeley: University of CA Press, 43–51.
## 95%/95% 2-sided linear regression tolerance bounds ## for a sample of size 100. set.seed(100) x <- runif(100, 0, 10) y <- 20 + 5*x + rnorm(100, 0, 3) out <- regtol.int(reg = lm(y ~ x), new.x = cbind(c(3, 6, 9)), side = 2, alpha = 0.05, P = 0.95) plottol(out, x = cbind(1, x), y = y, side = "two", x.lab = "X", y.lab = "Y")