Computation of the survival function of the Run Length (RL) for EWMA control charts monitoring normal variance.
sewma.sf(n, l, cl, cu, sigma, df, hs=1, sided="upper", r=40, qm=30)Returns a vector which resembles the survival function up to a certain point.
calculate sf up to value n.
smoothing parameter lambda of the EWMA control chart.
lower control limit of the EWMA control chart.
upper control limit of the EWMA control chart.
true standard deviation.
actual degrees of freedom, corresponds to subgroup size (for known mean it is equal to the subgroup size, for unknown mean it is equal to subgroup size minus one.
so-called headstart (enables fast initial response).
distinguishes between one- and two-sided two-sided
EWMA-\(S^2\) control charts
by choosing "upper" (upper chart without reflection at cl --
the actual value of cl is not used),
"Rupper" (upper chart with reflection at cl), "Rlower"
(lower chart with reflection at cu),
and "two" (two-sided chart), respectively.
dimension of the resulting linear equation system (highest order of the collocation polynomials).
number of quadrature nodes for calculating the collocation definite integrals.
Sven Knoth
The survival function P(L>n) and derived from it also the cdf P(L<=n) and the pmf P(L=n) illustrate the distribution of the EWMA run length. For large n the geometric tail could be exploited. That is, with reasonable large n the complete distribution is characterized. The algorithm is based on Waldmann's survival function iteration procedure and on results in Knoth (2007).
S. Knoth (2007), Accurate ARL calculation for EWMA control charts monitoring simultaneously normal mean and variance, Sequential Analysis 26, 251-264.
K.-H. Waldmann (1986), Bounds for the distribution of the run length of geometric moving average charts, Appl. Statist. 35, 151-158.
sewma.arl for zero-state ARL computation of variance EWMA control charts.