Confidence Intervals for 'mblm' Model
Computes confidence intervals for one or more parameters in a fitted model of 'mblm' class.
## S3 method for class 'mblm' confint(object, parm, level = 0.95, ...)
object |
a fitted model object |
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. Not yet implemented for 'mblm' |
level |
the confidence level required |
... |
additional arguments |
This function computes confidence intervals for slope and intercept in linear model based on single median or repeated medians. The confidence intervals are computed in simpliest way, as confidence interval for the median of all slopes or intercepts found during fitting.
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter.
The recommended method of calculating confidence intervals, given by Sen and based on Kendall's tau, not Wilcoxon test, is not implemented at this time and is considered to be implemented in next version of this package.
Lukasz Komsta
Sen, P.K. (1968). Estimates of Regression Coefficient Based on Kendall's tau. J. Am. Stat. Ass. 63, 324, 1379-1389.
set.seed(1234) x <- 1:100+rnorm(100) y <- x+rnorm(100) y[100] <- 200 fit <- mblm(y~x) fit summary(fit) confint(fit)
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