R语言 sampling包 samplecube()函数中文帮助文档(中英文对照)

loveR · 发表于 2012-9-29 21:50:19

samplecube(sampling)
samplecube()所属R语言包：sampling

 Sample cube method
 示例立方体方法

 译者：生物统计家园网机器人LoveR

描述----------Description----------

Selects a balanced sample (a vector of 0 and 1) or an almost balanced sample. Firstly, the flight phase is applied. Next, if needed, the landing phase is applied on the result of the flight phase.
选择均衡的样本（0和1）的向量或几乎均衡的样本。首先被施加的飞行阶段。接着，如果需要的话，着陆阶段施加在飞行阶段的结果。

用法----------Usage----------

samplecube(X,pik,order=1,comment=TRUE,method=1)

参数----------Arguments----------

参数：X
matrix of auxiliary variables on which the sample must be balanced.
该样本必须是平衡的辅助变量的矩阵。

参数：pik
vector of inclusion probabilities.
矢量包含概率。

参数：order
1, the data are randomly arranged, 2, no change in data order, 3, the data are sorted in decreasing order.
数据1，数据是随机排列，参考2，没有变化的数据的顺序，参考3，以递减的顺序进行排序。

参数：comment
a comment is written during the execution if comment is TRUE.
在执行过程中如果comment是TRUE写评论。

参数：method
1, for a landing phase by linear programming, 2, for a landing phase by suppression of variables.
如图1所示，通过线性规划，参考2，为着陆阶段通过抑制变量为着陆阶段。

参考文献----------References----------

Chauvet, G. and Till茅, Y. (2006). A fast algorithm of balanced sampling. Computational Statistics, 21/1:53–62. Chauvet, G. and Till茅, Y. (2005). New SAS macros for balanced sampling. In INSEE, editor, Journ茅es de M茅thodologie Statistique, Paris. Deville, J.-C. and Till茅, Y. (2004). Efficient balanced sampling: the cube method. Biometrika, 91:893–912. Deville, J.-C. and Till茅, Y. (2005). Variance approximation under balanced sampling. Journal of Statistical Planning and Inference, 128/2:411–425.

参见----------See Also----------

landingcube, fastflightcube
landingcube，fastflightcube

实例----------Examples----------

############[＃＃＃＃＃＃＃＃＃＃＃]
## Example 1[＃示例1]
############[＃＃＃＃＃＃＃＃＃＃＃]
# matrix of balancing variables[矩阵的平衡变量]
X=cbind(c(1,1,1,1,1,1,1,1,1),c(1.1,2.2,3.1,4.2,5.1,6.3,7.1,8.1,9.1))
# vector of inclusion probabilities[包含概率向量]
# the sample size is 3.[样本大小为3。]
pik=c(1/3,1/3,1/3,1/3,1/3,1/3,1/3,1/3,1/3)
# selection of the sample[样品的选择]
s=samplecube(X,pik,order=1,comment=TRUE)
# The selected sample[所选样本]
(1:length(pik))[s==1]
############[＃＃＃＃＃＃＃＃＃＃＃]
## Example 2[＃示例2]
############[＃＃＃＃＃＃＃＃＃＃＃]
# 2 strata and 2 auxiliary variables[2地层和2个辅助变量]
# we verify the values of the inclusion probabilities by simulations[我们通过仿真验证的值包含概率]
X=rbind(c(1,0,1,2),c(1,0,2,5),c(1,0,3,7),c(1,0,4,9),
c(1,0,5,1),c(1,0,6,5),c(1,0,7,7),c(1,0,8,6),c(1,0,9,9),
c(1,0,10,3),c(0,1,11,3),c(0,1,12,2),c(0,1,13,3),
c(0,1,14,6),c(0,1,15,8),c(0,1,16,9),c(0,1,17,1),
c(0,1,18,2),c(0,1,19,3),c(0,1,20,4))
pik=rep(1/2,times=20)
ppp=rep(0,times=20)
sim=100 #for accurate results increase this value[准确的结果增加值]
for(i in (1:sim))
ppp=ppp+samplecube(X,pik,1,FALSE)
ppp=ppp/sim
print(ppp)
print(pik)
############[＃＃＃＃＃＃＃＃＃＃＃]
## Example 3[＃示例3]
############[＃＃＃＃＃＃＃＃＃＃＃]
# unequal probability sampling by cube method[立方体不等概率抽样的方法]
# one auxiliary variable equal to the inclusion probability[一个辅助变量等于包含概率]
N=200
pik=runif(N)
pikfin=samplecube(array(pik,c(N,1)),pik,1,TRUE)
############ [＃＃＃＃＃＃＃＃＃＃＃]
## Example 4[＃例4]
############[＃＃＃＃＃＃＃＃＃＃＃]
# p auxiliary variables generated randomly[p辅助变量随机产生]
N=1000
p=7
x=rnorm(N*p,10,3)
# random inclusion probabilities [随机列入概率的]
pik= runif(N)
X=array(x,c(N,p))
X=cbind(cbind(X,rep(1,times=N)),pik)
pikfin=samplecube(X,pik,1,TRUE)
############ [＃＃＃＃＃＃＃＃＃＃＃]
## Example 5[＃例5]
############[＃＃＃＃＃＃＃＃＃＃＃]
# strata and an auxiliary variable[阶层和辅助变量]
N=5000
a=rep(1,times=N)
b=rep(0,times=N)
V1=c(a,b,b)
V2=c(b,a,b)
V3=c(b,b,a)
X=cbind(V1,V2,V3)
pik=rep(2/10,times=3*N)
pikfin=samplecube(X,pik,1,TRUE)
############[＃＃＃＃＃＃＃＃＃＃＃]
## Example 6[＃例6]
############[＃＃＃＃＃＃＃＃＃＃＃]
# Selection of a balanced sample using the MU284 population,[选择一个平衡样本使用MU284人口，]
# simulation and comparison of the variance with[模拟和比较的方差与]
# unequal probability sampling of fixed sample size.[固定样本量的不等概率抽样。]
############[＃＃＃＃＃＃＃＃＃＃＃]
data(MU284)
# Computation of the inclusion probabilities[包含概率的计算]
pik=inclusionprobabilities(MU284$P75,50)
# Definition of the matrix of balancing variables[的平衡变量矩阵定义]
X=cbind(MU284$P75,MU284$CS82,MU284$SS82,MU284$S82,MU284$ME84,MU284$REV84)
# Computation of the Horvitz-Thompson estimator for a balanced sample[计算一个平衡的样品的的霍维茨-Thompson估计]
s=samplecube(X,pik,1,FALSE)
HTestimator(MU284$RMT85[s==1],pik[s==1])
# Computation of the Horvitz-Thompson estimator for an unequal probability sample[计算的不等概率抽样的的霍维茨-Thompson估计]
s=samplecube(matrix(pik),pik,1,FALSE)
HTestimator(MU284$RMT85[s==1],pik[s==1])
# simulations; for a better accurancy, increase the value of 'sim'[模拟一个更好的之准确度，增加值的SIM“]
sim=8
res1=rep(0,times=sim)
res2=rep(0,times=sim)
for(i in 1:sim)
{
cat("Simulation number ",i,"\n")
s=samplecube(X,pik,1,FALSE)
res1[i]=HTestimator(MU284$RMT85[s==1],pik[s==1])
s=samplecube(matrix(pik),pik,1,FALSE)
res2[i]=HTestimator(MU284$RMT85[s==1],pik[s==1])
}
# summary and boxplots[总结和盒状图]
summary(res1)
summary(res2)
ss=cbind(res1,res2)
colnames(ss) = c("balanced sampling","uneq prob sampling")
boxplot(data.frame(ss), las=1)

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