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Greg (version 2.0.2)

hatvalues.ols: Get the hat matrix for the OLS

Description

The hat matrix comes from the residual definition: $$\hat{\epsilon} = y-X\hat{\beta} = \{I_n-X(X'X)X'\}y = (I_n-H)y$$ where the H is called the hat matrix since $$Hy = \hat{y}$$. The hat values are actually the diagonal elements of the matrix that sum up to p (the rank of X, i.e. the number of parameters + 1). See ols.influence().

Usage

# S3 method for ols
hatvalues(model, ...)

Value

vector

Arguments

model

The ols model fit

...

arguments passed to methods.

Examples

Run this code
# Generate some data
n <- 500
x1 <- runif(n) * 2
x2 <- runif(n)
y <- x1^3 + x2 + rnorm(n)

library(rms)
library(sandwich)
dd <- datadist(x1, x2, y)
org.op <- options(datadist = "dd")

# Main function
f <- ols(y ~ rcs(x1, 3) + x2)

# Check the bread
bread(f)
# Check the HC-matrix
vcovHC(f, type = "HC4m")
# Adjust the model so that it uses the HC4m variance
f_rob <- robcov_alt(f, type = "HC4m")
# Get the new HC4m-matrix
# - this function just returns the f_rob$var matrix
vcov(f_rob)
# Now check the confidence interval for the function
confint(f_rob)

options(org.op)

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