sigma2epsilon: Error Variance sigma_{\varepsilon}^{2}
In jeksterslabds/jeksterslabRlinreg: Jekster's Lab Linear Regression Utilities

Description Usage Arguments Author(s) See Also Examples

Error variance σ_{\varepsilon}^{2} from the slopes \boldsymbol{β}_{2, \cdots, k} and variance-covariance matrix \boldsymbol{Σ}.

1	sigma2epsilon(slopes, sigma2y, sigmayX, SigmaX)

`slopes`	Numeric vector of length `p` or `p` by `1` matrix. p \times 1 column vector of regression slopes ≤ft( \boldsymbol{β}_{2, 3, \cdots, k} = ≤ft\{ β_2, β_3, \cdots, β_k \right\} \right) .
`sigma2y`	Numeric. Variance of the regressand variable ≤ft( σ_{y}^{2} \right).
`sigmayX`	Numeric vector of length `p` or `p` by `1` matrix. p \times 1 vector of covariances between the regressand y variable and regressor variables X_2, X_3, \cdots, X_k ≤ft( \boldsymbol{σ}_{\mathbf{y}, \mathbf{X}} = ≤ft\{ σ_{y, X_2}, σ_{y, X_3}, \cdots, σ_{y, X_k} \right\}^{T} \right).
`SigmaX`	`p` by `p` numeric matrix. p \times p matrix of variances and covariances between regressor variables {X}_{2}, {X}_{3}, \cdots, {X}_{k} ≤ft( \boldsymbol{Σ}_{\mathbf{X}} \right).

Ivan Jacob Agaloos Pesigan

Other parameter functions: .intercept(), .slopesprime(), .slopes(), intercept(), slopesprime(), slopes()

slopes <- c(0.2076475, 0.4510391)
sigma2y <- 1.288163
sigmayX <- c(0.4661224, 0.5771429)
SigmaX <- matrix(
  data = c(1.2934694, 0.4379592, 0.4379592, 1.0779592),
  ncol = 2
)
sigma2epsilon(slopes = slopes, sigma2y = sigma2y, sigmayX = sigmayX, SigmaX = SigmaX)