fkde: Estimate Asymptotic Joint Distribution of EWMA variables
In gb: Generalize Lambda Distribution and Generalized Bootstrapping
Description
Usage
Arguments
Author(s)
References
Description
Estimate Asymptotic Joint Distribution of EWMA variables
for control chart.
Usage
1
2
fkde(n=5, pm0=0.5, pI0=0.2, lambda=0.05,
gridsize=100,B=10000,T=10000)
Arguments
n
sample size.
lambda
a parameter to compute EWMA
pm0,pI0
in-control parameters for the control
chart.
gridsize
gridsize to evalue the joint PDF values
B, T
iteration times and maximum time of t to
generate random samples for density estimation
Author(s)
B. Wang bwang@southalabama.edu
References
Yang, S.F. and Wang, B. “Using A Kernel Control Region to Monitor
Both the Process Location and Dispersion”.
gb documentation built on May 2, 2019, 5:31 a.m.
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Description Usage Arguments Author(s) References
Description
Estimate Asymptotic Joint Distribution of EWMA variables for control chart.
Usage
1 2 | fkde(n=5, pm0=0.5, pI0=0.2, lambda=0.05,
gridsize=100,B=10000,T=10000)
|
Arguments
n |
sample size. |
lambda |
a parameter to compute EWMA |
pm0,pI0 |
in-control parameters for the control chart. |
gridsize |
gridsize to evalue the joint PDF values |
B, T |
iteration times and maximum time of |
Author(s)
B. Wang bwang@southalabama.edu
References
Yang, S.F. and Wang, B. “Using A Kernel Control Region to Monitor Both the Process Location and Dispersion”.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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