Analysis of Variance (from \(RSS\) and \(ESS\))

Analysis of Variance (from \(RSS\) and \(ESS\))

.anovatable(RSS = NULL, ESS = NULL, n, k, X, y)

Arguments

RSS	Numeric. Residual sum of squares.
ESS	Numeric. Explained sum of squares.
n	Integer. Sample size.
k	Integer. Number of regressors including a regressor whose value is 1 for each observation.
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.

Value

Returns the ANOVA table.

See also

Other hypothesis testing functions: anovatable(), ci(), nhst()

Author

Ivan Jacob Agaloos Pesigan

Ivan Jacob Agaloos Pesigan