n.times.eVar.of.HL2

<p>n times the empirical variances of the Hodges-Lehmann estimator (HL2) 
under the standard normal distribution, 
where $n$ is the sample size and $n$ is from 1 to 100.
For the HL2, the median is taken
over $i \le j$ where $i,j=1,2,\ldots,n$,
that is,
$$\mathrm{HL2} = \mathop{\mathrm{median}}_{i \le j}\Big(\frac{X_i+X_j}{2} \Big).$$
They are obtained using the extensive Monte Carlo simulation
with 1E07 replicates.</p>

datasets

Variance

Constructs robust quality control chart based on the median and Hodges-Lehmann estimators (location) and the median absolute deviation (MAD) and Shamos estimators (scale) which are unbiased with a sample of finite size. For more details, see Park, Kim and Wang (2019)<arXiv:1908.00462>. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. NRF-2017R1A2B4004169).

Chanseok Park

rQCC

Robust Quality Control Chart

Min Wang

n.times.eVar.of.HL2 function

<p>This data frame contains 100 values.</p>

n.times.eVar.of.HL2: Empirical variances of the Hodges-Lehmann (HL2) estimator (times n)

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