Calculate statistical measures for the inverse Gaussian control chart

This function calculates various statistical measures for the inverse Gaussian control chart.

Usage

stats_ig(data, alpha = 0.0027, mu = NULL, lambda = NULL, ...)

Arguments

data: The data matrix.
alpha: The significance level.
mu: The mean parameter of the distribution (optional).
lambda: The shape parameter of the distribution (optional).
...: Additional arguments to be passed to the limits function.

Value

A list containing the estimated parameters, alpha-hat, ARL, MRL, SDRL, control limits, convergence status, and value of the objective function.

Examples

set.seed(0)
x <- r_ig(lots = 1000, n = 10, mu = 1, lambda = 1.7)

# Estimate for maximum likelihood
stats_ig(data = x)
#> $mu_hat
#> [1] 0.9923649
#> 
#> $lambda_hat
#> [1] 1.861464
#> 
#> $alpha_hat
#> [1] 0
#> 
#> $ARL
#> [1] Inf
#> 
#> $MRL
#> [1] -Inf
#> 
#> $SDRL
#> [1] Inf
#> 
#> $li
#> [1] 0.4929123
#> 
#> $ls
#> [1] 1.902939
#> 
#> $convergence
#> [1] 0
#> 
#> $value
#> [1] -93.64581
#> 

# Using the true parameters
stats_ig(data = x, mu = 1, lambda = 1.7)
#> $mu_hat
#> [1] 1
#> 
#> $lambda_hat
#> [1] 1.7
#> 
#> $alpha_hat
#> [1] 0
#> 
#> $ARL
#> [1] Inf
#> 
#> $MRL
#> [1] -Inf
#> 
#> $SDRL
#> [1] Inf
#> 
#> $li
#> [1] 0.4798106
#> 
#> $ls
#> [1] 1.97604
#> 
#> $convergence
#> NULL
#> 
#> $value
#> NULL
#>