calm: Calibrated inference for linear models

In rothenhaeusler/calinf: Calibrated inference: inference that accounts for both sampling and distributional uncertainty

Calibrated inference for linear models

Description

Calibrated inference for linear models

Usage

calm(formulas, data, target, ...)

Arguments

formulas	A list of formulas
data	A dataframe containing the variables in the model

Examples

n <- 1000
X <- rnorm(n)
Z1 <- rnorm(n)
Z2 <- rnorm(n)
Y <- 1*X + X^2 + Z1 + Z2 + rnorm(n)
df <- data.frame(cbind(X,Y,Z1,Z2))
data <- as.data.frame(cbind(Y,X))
formulas <- list(Y~X, Y ~ X + I(X^2), Y ~ X + Z1, Y ~ X + Z2 + I(X^2), Y ~ X + Z1 + Z2 + I(X^2))
calm(formulas,data=data, target="X")
summary(lm(Y ~ X + Z1 + Z2 + I(X^2), data=df))

rothenhaeusler/calinf documentation built on May 2, 2022, 12:44 p.m.