Residual Plots

residual.plot(X, y)

Arguments

X

n by k numeric matrix. The data matrix \(\mathbf{X}\) (also known as design matrix, model matrix or regressor matrix) is an \(n \times k\) matrix of \(n\) observations of \(k\) regressors, which includes a regressor whose value is 1 for each observation on the first column.

y

Numeric vector of length n or n by 1 matrix. The vector \(\mathbf{y}\) is an \(n \times 1\) vector of observations on the regressand variable.

See also

Other plotting functions: scatter.plot()

Author

Ivan Jacob Agaloos Pesigan

Examples

# Simple regression------------------------------------------------ X <- jeksterslabRdatarepo::wages.matrix[["X"]] X <- X[, c(1, ncol(X))] y <- jeksterslabRdatarepo::wages.matrix[["y"]] residual.plot(X = X, y = y)
# Multiple regression---------------------------------------------- X <- jeksterslabRdatarepo::wages.matrix[["X"]] # age is removed X <- X[, -ncol(X)] residual.plot(X = X, y = y)