Calculate statistical measures for a Beta Prime control chart

Usage

stats_bp(data, alpha = 0.0027, mu = NULL, phi = NULL, ...)

Arguments

data: A matrix of observed data
alpha: The significance level for the control limits
mu: The mean parameter of the Beta Prime distribution (optional)
phi: The shape parameter of the Beta Prime distribution (optional)
...: Additional arguments to be passed to limits_bp

Value

A list containing the estimated parameters, control limits, and statistical measures

Examples

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

# Estimate for maximum likelihood
stats_bp(data = x, alpha = 0.0027)
#> $mu_hat
#> [1] 1.010626
#> 
#> $phi_hat
#> [1] 1.720167
#> 
#> $alpha_hat
#> [1] 0.003
#> 
#> $ARL
#> [1] 333.3333
#> 
#> $MRL
#> [1] 230.7023
#> 
#> $SDRL
#> [1] 332.833
#> 
#> $li
#> [1] 0.4083773
#> 
#> $ls
#> [1] 2.798659
#> 
#> $convergence
#> [1] 0
#> 
#> $value
#> [1] 222.763
#> 

# Useing the true parameters
stats_bp(data = x, alpha = 0.0027, mu = 1, phi = 1.7)
#> $mu_hat
#> [1] 1
#> 
#> $phi_hat
#> [1] 1.7
#> 
#> $alpha_hat
#> [1] 0.003
#> 
#> $ARL
#> [1] 333.3333
#> 
#> $MRL
#> [1] 230.7023
#> 
#> $SDRL
#> [1] 332.833
#> 
#> $li
#> [1] 0.401327
#> 
#> $ls
#> [1] 2.791344
#> 
#> $convergence
#> NULL
#> 
#> $value
#> NULL
#>