linreg: Linear Regression

In jeksterslabds/jeksterslabRlinreg: Jekster's Lab Linear Regression Utilities

Description

Linear Regression

Usage

linreg(
  X,
  y,
  varnamesX = NULL,
  varnamey = NULL,
  qr = TRUE,
  sehatbetahattype = "unbiased",
  sehatslopeshatprimetype = "delta",
  adjust = FALSE,
  plot = TRUE,
  print = TRUE
)

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.
varnamesX	Optional. Character vector of length k. Variable names for matrix X.
varnamey	Optional. Character string. Variable name for vector y.
qr	Logical. If TRUE, use QR decomposition when normal equations fail. If FALSE, use singular value decompositon when normal equations fail.
sehatbetahattype	Character string. Standard errors for regression coefficients hypothesis test. Options are sehatbetahattype = "unbiased" and sehatbetahattype = "biased".
sehatslopeshatprimetype	Character string. Standard errors for standardized regression slopes hypothesis test. Options are sehatslopeshatprimetype = "textbook" and sehatslopeshatprimetype = "delta".
adjust	Logical. If sehatslopeshatprimetype = "delta" and adjust = TRUE, uses n - 3 to adjust sehatslopeshatprime for bias. This adjustment is recommended for small sample sizes.
plot	Logical. Display plots.
print	Logical. Display summary output.

Author(s)

Ivan Jacob Agaloos Pesigan

Examples

# Simple regression------------------------------------------------
X <- jeksterslabRdatarepo::wages.matrix[["X"]]
X <- X[, c(1, ncol(X))]
y <- jeksterslabRdatarepo::wages.matrix[["y"]]
linreg(X = X, y = y)

# Multiple regression----------------------------------------------
X <- jeksterslabRdatarepo::wages.matrix[["X"]]
# age is removed
X <- X[, -ncol(X)]
linreg(X = X, y = y)

# Multiple regression----------------------------------------------
# delta standard errors for standardized coefficients
linreg(X = X, y = y, sehatslopeshatprimetype = "delta")

jeksterslabds/jeksterslabRlinreg documentation built on Jan. 7, 2021, 8:30 a.m.