mutheta: Model-Implied Mean Vector \boldsymbol{mu} <=ft(...

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

Description

Model-implied mean vector \boldsymbol{μ} ≤ft( \boldsymbol{θ} \right) from parameters of a k-variable linear regression model.

Usage

mutheta(beta, muX)

Arguments

beta	Numeric vector of length k or k by 1 matrix. k \times 1 vector of regression coefficients ≤ft( \boldsymbol{β} \right).
muX	Numeric vector of length p or p by 1 matrix. p \times 1 column vector of means of the regressors {X}_{2}, {X}_{3}, \cdots, {X}_{k} ≤ft( \boldsymbol{μ}_{\mathbf{X}} \right) .

Details

The following are the parameters of a linear regression model for the mean structure

• \boldsymbol{β} is the k \times 1 column vector of regression coefficients, and

• \boldsymbol{μ}_{\mathbf{X}} is the p \times 1 column vector of means of the regressors {X}_{2}, {X}_{3}, \cdots, {X}_{k} .

Value

Returns the model-implied mean vector \boldsymbol{μ} ≤ft( \boldsymbol{θ} \right). Note that the first item corresponds to the expected value of y. The rest of the items correspond to muX.

Author(s)

Ivan Jacob Agaloos Pesigan

See Also

Other model-implied functions: Sigmatheta()

Examples

beta <- c(-12.7128845, 0.2076475, 0.4510391)
muX <- c(70.18, 3.06)
mutheta(beta = beta, muX = muX)

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