xsewma.arl(spc)
xsewma.arl()所属R语言包：spc
Compute ARLs of simultaneous EWMA control charts (mean and variance charts)
计算连串长度的同时EWMA控制图（均值和方差图）
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Computation of the (zero-state) Average Run Length (ARL) for different types of simultaneous EWMA control charts (based on the sample mean and the sample variance S^2)
计算（零状态），平均运行长度（ARL）为不同类型的同时EWMA控制图（根据样本均值和样本方差S^2）
用法----------Usage----------
xsewma.arl(lx, cx, ls, csu, df, mu, sigma, hsx=0, Nx=40, csl=0, hss=1, Ns=40, s2.on=TRUE, sided="upper", qm=30)
参数----------Arguments----------
参数：lx
smoothing parameter lambda of the two-sided mean EWMA chart.
平滑参数λ为双面的平均EWMA图。
参数：cx
control limit of the two-sided mean EWMA control chart.
双面平均EWMA控制图的控制界限。
参数：ls
smoothing parameter lambda of the variance EWMA chart.
平滑参数lambda值的方差EWMA图。
参数：csu
upper control limit of the variance EWMA control chart.
方差的EWMA控制图的控制上限。
参数：df
actual degrees of freedom, corresponds to batch size.
实际自由度，对应的批次大小。
参数：mu
true mean.
真正的意思。
参数：sigma
true standard deviation.
真正的标准偏差。
参数：hsx
so-called headstart (give fast initial response) of the mean chart – do not confuse with the true FIR feature considered in xewma.arl; will be updated.
所谓的领先地位提供快速初始响应的平均图表 - 不要混淆与真正的FIR考虑xewma.arl的功能;将被更新。
参数：Nx
dimension of the approximating matrix of the mean chart.
的平均图表的近似矩阵的维数。
参数：csl
lower control limit of the variance EWMA control chart; default value is 0; not considered if sided is "upper".
方差的EWMA控制图的控制下限的默认值是0，如果不考虑sided是"upper"。
参数：hss
headstart (give fast initial response) of the variance chart.
领先地位提供快速初始响应的差异图。
参数：Ns
dimension of the approximating matrix of the variance chart.
的方差的图表近似矩阵的维数。
参数：s2.on
distinguish between S^2 and S chart.
区分S^2和S图。
参数：sided
distinguish 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.
区分和双面双面EWMA-S^2控制图的"upper"（上图没有反映cl - cl是实际值未使用），"Rupper"（上图反映在cl）"Rlower"（下图反映在cu），和"two"（2双面图表），分别。
参数：qm
number of quadrature nodes used for the collocation integrals.
搭配的积分用于正交节点的数量。
Details
详细信息----------Details----------
xsewma.arl determines the Average Run Length (ARL) by an extension of Gan's (derived from ideas already published by Waldmann) algorithm. The variance EWMA part is treated similarly to the ARL calculation method deployed for the single variance EWMA chartas in Knoth (2005), that is, by means of
xsewma.arl确定的平均运行长度（ARL）由甘（得从观念已经发表的沃达迈）算法的扩展。的方差EWMA控制部同样地对待部署单方差EWMA chartas Knoth（2005），即，ARL计算方法借助于
值----------Value----------
Returns a single value which resembles the ARL.
返回一个单一的值，类似于ARL。
（作者）----------Author(s)----------
Sven Knoth
参考文献----------References----------
K. Waldmann (1986), Bounds for the distribution of the run length of geometric moving average charts, J. R. Stat. Soc., Ser. C, Appl. Stat. 35, 151-158.
F. F. Gan (1995), Joint monitoring of process mean and variance using exponentially weighted moving average control charts, Technometrics 37, 446-453.
S. Knoth (2005), Accurate ARL computation for EWMA-<code>S^2</code> control charts, Statistics and Computing 15, 341-352.
S. Knoth (2007), Accurate ARL calculation for EWMA control charts monitoring simultaneously normal mean and variance, Sequential Analysis 26, 251-264.
参见----------See Also----------
xewma.arl and sewma.arl for zero-state ARL computation of single mean and variance EWMA control charts, respectively.
xewma.arl和sewma.arlARL单一的均值和方差的EWMA控制图，分别计算零状态。
实例----------Examples----------
## Knoth (2007)[＃Knoth（2007年）]
## collocation results in Table 1[结果见表1＃搭配]
## Monte Carlo with 10^9 replicates: 252.307 +/- 0.0078[＃蒙地卡罗10 ^ 9个重复：252.307 + / - 0.0078]
# process parameters[工艺参数]
mu <- 0
sigma <- 1
# batch size n=5, df=n-1[批量大小为n = 5，DF = N-1]
df <- 4
# lambda of mean chart[lambda值的平均图]
lx <- .134
# c_mu^* = .345476571 = cx/sqrt(n) * sqrt(lx/(2-lx)[c_mu ^ * = 0.345476571 = CX / SQRT（N）* SQRT（LX /（2-LX）]
cx <- .345476571*sqrt(df+1)/sqrt(lx/(2-lx))
# lambda of variance chart[lambda值的方差图]
ls <- .1
# c_sigma = .477977[c_sigma = 0.477977]
csu <- 1 + .477977
# matrix dimensions for mean and variance part[矩阵尺寸的均值和方差的一部分]
Nx <- 25
Ns <- 25
# mode of variance chart[模式的差异图]
SIDED <- "upper"
arl <- xsewma.arl(lx, cx, ls, csu, df, mu, sigma, Nx=Nx, Ns=Ns, sided=SIDED)
arl
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注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-9-30 14:34:05
