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Estimating equations for the mean and variance

Source: R/ee-basic.R
ee_mean_variance.Rd

Returns a 2-by-n matrix of estimating equation contributions for the mean and variance: $$\psi_i(\theta) = \begin{pmatrix} Y_i - \theta_1 \\ (Y_i - \theta_1)^2 - \theta_2 \end{pmatrix}$$

Usage

ee_mean_variance(theta, y)

Arguments

theta

Numeric vector of length 2. theta[1] is the mean, theta[2] is the variance.

y

Numeric vector of observed values.

Value

A 2-by-n matrix, with rows named mean and variance.

Examples

y <- c(1, 2, 3, 1, 4, 5, 3, 2, 6, 7)
psi <- function(theta) ee_mean_variance(theta, y = y)
m <- m_estimate(stacked_equations = psi, init = c(0, 1))
coef(m)
#>     mean variance 
#>     3.40     3.84