R version 4.0.2 (2020-06-22) -- "Taking Off Again"
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> library(survey)
Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Attaching package: ‘survey’
The following object is masked from ‘package:graphics’:
dotchart
> set.seed(42)
>
> df<-data.frame(x=exp(rnorm(1000)))
> df$y<-round(df$x,1)
> ddf<-svydesign(id=~1,data=df)
Warning message:
In svydesign.default(id = ~1, data = df) :
No weights or probabilities supplied, assuming equal probability
> rdf<-as.svrepdesign(ddf)
>
> SE(oldsvyquantile(~x,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE))
0.01 0.1 0.5 0.9 0.99
0.01543792 0.01264453 0.03386225 0.16131948 2.10605799
>
> SE(oldsvyquantile(~x,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE))
x
q0.01 0.01554946
q0.1 0.01425828
q0.5 0.03428012
q0.9 0.16457488
q0.99 1.88672412
>
> SE(oldsvyquantile(~x,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,df=Inf))
0.01 0.1 0.5 0.9 0.99
0.01545209 0.01265608 0.03388011 0.16145776 2.10061576
>
> SE(oldsvyquantile(~x,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,df=Inf))
x
q0.01 0.01556240
q0.1 0.01420086
q0.5 0.03430175
q0.9 0.16461019
q0.99 1.88818131
>
>
> oldsvyquantile(~y,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,ties="rounded",interval.type="betaWald")
$quantiles
0.01 0.1 0.5 0.9 0.99
y 0.02352941 0.2230769 0.9340909 3.55 9.4
$CIs
, , y
0.01 0.1 0.5 0.9 0.99
(lower 0.01594200 0.2020115 0.8578143 3.207543 7.568142
upper) 0.03287947 0.2467045 1.0059815 3.862241 14.978632
>
> oldsvyquantile(~y,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE)
Statistic:
y
q0.01 0.1
q0.1 0.3
q0.5 1.0
q0.9 3.6
q0.99 9.4
SE:
y
q0.01 0.02547977
q0.1 0.02547977
q0.5 0.02547977
q0.9 0.15287859
q0.99 1.88302540
>
> oldsvyquantile(~y,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,ties="rounded",interval.type="betaWald",df=Inf)
$quantiles
0.01 0.1 0.5 0.9 0.99
y 0.02352941 0.2230769 0.9340909 3.55 9.4
$CIs
, , y
0.01 0.1 0.5 0.9 0.99
(lower 0.01594200 0.2020115 0.8578143 3.207543 7.568142
upper) 0.03287947 0.2467045 1.0059815 3.862241 14.978632
>
> oldsvyquantile(~y,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE, df=Inf)
Statistic:
y
q0.01 0.1
q0.1 0.3
q0.5 1.0
q0.9 3.6
q0.99 9.4
SE:
y
q0.01 0.02551067
q0.1 0.02551067
q0.5 0.02551067
q0.9 0.15306404
q0.99 1.88450896
>
>
>
> df<-data.frame(x=exp(rnorm(20)))
> df$y<-round(df$x,1)
> ddf<-svydesign(id=~1,data=df)
Warning message:
In svydesign.default(id = ~1, data = df) :
No weights or probabilities supplied, assuming equal probability
> rdf<-as.svrepdesign(ddf)
> SE(oldsvyquantile(~x,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE))
0.01 0.1 0.5 0.9 0.99
0.03576771 0.07329496 0.30149917 2.03440784 1.88468597
>
> SE(oldsvyquantile(~x,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE))
x
q0.01 0.00000000
q0.1 0.04598541
q0.5 0.25943731
q0.9 2.12343073
q0.99 1.91998924
>
> SE(oldsvyquantile(~x,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,df=Inf))
0.01 0.1 0.5 0.9 0.99
0.03637398 0.07470310 0.29938115 2.16381289 2.00708994
>
> SE(oldsvyquantile(~x,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,df=Inf))
x
q0.01 0.00000000
q0.1 0.04732818
q0.5 0.24957966
q0.9 2.25211815
q0.99 2.04043154
>
>
> oldsvyquantile(~y,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,ties="rounded",interval.type="betaWald")
$quantiles
0.01 0.1 0.5 0.9 0.99
y 0.1 0.15 0.75 2.4 8.68
$CIs
, , y
0.01 0.1 0.5 0.9 0.99
(lower 0.100000 0.1000000 0.3674054 1.352279 0.5674674
upper) 1.132533 0.3464541 1.6303784 8.473337 10.2000000
>
> oldsvyquantile(~y,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE)
Statistic:
y
q0.01 0.10
q0.1 0.20
q0.5 0.80
q0.9 2.40
q0.99 8.68
SE:
y
q0.01 0.00000000
q0.1 0.02611112
q0.5 0.26542051
q0.9 2.10908603
q0.99 1.91777710
>
> oldsvyquantile(~y,ddf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE,ties="rounded",interval.type="betaWald",df=Inf)
$quantiles
0.01 0.1 0.5 0.9 0.99
y 0.1 0.15 0.75 2.4 8.68
$CIs
, , y
0.01 0.1 0.5 0.9 0.99
(lower 0.100000 0.1000000 0.3674054 1.352279 0.5674674
upper) 1.132533 0.3464541 1.6303784 8.473337 10.2000000
>
> oldsvyquantile(~y,rdf, c(0.01,0.1,0.5,0.9,0.99),ci=TRUE, df=Inf)
Statistic:
y
q0.01 0.10
q0.1 0.20
q0.5 0.80
q0.9 2.40
q0.99 8.68
SE:
y
q0.01 0.00000000
q0.1 0.02551067
q0.5 0.25244616
q0.9 2.23558589
q0.99 2.03881114
>
> proc.time()
user system elapsed
1.791 0.148 2.936
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