R Under development (unstable) (2024-03-19 r86153 ucrt) -- "Unsuffered Consequences"
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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 
   2.48    0.31    2.78