ciMat: Matrix for confidence intervals

In Pmisc: Various Utilities for knitr and inla

Matrix for confidence intervals

Description

Produces a matrix suitable for multiplying by results of summary or predict functions to give confidence intervals of a desired quantile

Usage

ciMat(p = 0.95, se.fit = FALSE, df = NULL)

Arguments

p	coverage of confidence interval
se.fit	row names of result are 'fit' and 'se.fit'
df	degrees of freedom for t distribution, defaults to normal

Value

matrix with three columns (estimate, upper and lower bound of CI) and two rows

Examples

(myCiMat = ciMat(0.8))

clotting <- data.frame(
    u = c(5,10,15,20,30,40,60,80,100),
    lot1 = c(118,58,42,35,27,25,21,19,18),
    lot2 = c(69,35,26,21,18,16,13,12,12))
glmRes = stats::glm(lot1 ~ log(u), data = clotting, family = Gamma)
# CI on the natural scale
exp(summary(glmRes)$coef[,rownames(myCiMat)] %*% myCiMat)

(myCiMatPred = ciMat(0.99, se.fit=TRUE))
glmPred = do.call(cbind,stats::predict(glmRes, se.fit=TRUE))
exp(glmPred[,rownames(myCiMatPred)] %*% myCiMatPred)

Pmisc documentation built on Feb. 14, 2024, 3 a.m.