simSample: Set up multiple samples

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/simSample.R

Description

A convenience wrapper for setting up multiple samples using setup with control class SampleControl.

Usage

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simSample(x, design = character(), grouping = character(), 
          collect = FALSE, fun = srs, size = NULL, 
          prob = NULL, ..., k = 1)

Arguments

x

the data.frame to sample from.

design

a character, logical or numeric vector specifying variables (columns) to be used for stratified sampling.

grouping

a character string, single integer or logical vector specifying a grouping variable (column) to be used for sampling whole groups rather than individual observations.

collect

logical; if a grouping variable is specified and this is FALSE (which is the default value), groups are sampled directly. If grouping variable is specified and this is TRUE, individuals are sampled in a first step. In a second step, all individuals that belong to the same group as any of the sampled individuals are collected and added to the sample. If no grouping variable is specified, this is ignored.

fun

a function to be used for sampling (defaults to srs). It should return a vector containing the indices of the sampled items (observations or groups).

size

an optional non-negative integer giving the number of items (observations or groups) to sample. For stratified sampling, a vector of non-negative integers, each giving the number of items to sample from the corresponding stratum.

prob

an optional numeric vector giving the probability weights, or a character string or logical vector specifying a variable (column) that contains the probability weights.

...

additional arguments to be passed to fun.

k

a single positive integer giving the number of samples to be set up.

Details

There are some restrictions on the argument names of the function supplied to fun. If it needs population data as input, the corresponding argument should be called x and should expect a data.frame. If the sampling method only needs the population size as input, the argument should be called N. Note that fun is not expected to have both x and N as arguments, and that the latter is much faster for stratified sampling or group sampling. Furthermore, if the function has arguments for sample size and probability weights, they should be called size and prob, respectively. Note that a function with prob as its only argument is perfectly valid (for probability proportional to size sampling). Further arguments of fun may be passed directly via the ... argument.

Value

An object of class "SampleSetup".

Author(s)

Andreas Alfons

See Also

setup, "SampleControl", "SampleSetup"

Examples

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data(eusilcP)

## simple random sampling
srss <- simSample(eusilcP, size = 20, k = 4)
summary(srss)
draw(eusilcP[, c("id", "eqIncome")], srss, i = 1)

## group sampling
gss <- simSample(eusilcP, grouping = "hid", size = 10, k = 4)
summary(gss)
draw(eusilcP[, c("hid", "id", "eqIncome")], gss, i = 2)

## stratified simple random sampling
ssrss <- simSample(eusilcP, design = "region", 
    size = c(2, 5, 5, 3, 4, 5, 3, 5, 2), k = 4)
summary(ssrss)
draw(eusilcP[, c("id", "region", "eqIncome")], ssrss, i = 3)

## stratified group sampling
sgss <- simSample(eusilcP, design = "region", 
    grouping = "hid", size = c(2, 5, 5, 3, 4, 5, 3, 5, 2), k = 4)
summary(sgss)
draw(eusilcP[, c("hid", "id", "region", "eqIncome")], sgss, i = 4)

Example output

Loading required package: Rcpp
Loading required package: lattice
Loading required package: parallel
4 samples of size 20 are set up
           id  eqIncome .weight
44781 0583701  7408.812  2932.7
55225 0908501 13150.719  2932.7
8929  2150303  5087.309  2932.7
57587 0663501 30261.224  2932.7
29927 1247901  8529.250  2932.7
15133 0536901 14579.030  2932.7
46794 0048001 20208.983  2932.7
22979 0131804 18798.567  2932.7
43668 2149904 25803.290  2932.7
21427 2324203  3728.690  2932.7
50488 1630503 19317.838  2932.7
25392 0675102 12960.508  2932.7
36412 2111106 14549.529  2932.7
54592 0790701 18187.348  2932.7
2801  1081101 16107.480  2932.7
20580 0344302 16844.455  2932.7
6794  2313002 13717.056  2932.7
47580 1426601 15439.830  2932.7
51349 0129001 12873.930  2932.7
35105 1615404 19390.895  2932.7
4 samples are set up

The sample sizes are:
[1] 16 23 30 23
        hid      id eqIncome .weight
54860  6760 0676001 22715.12    2500
54861  6760 0676002 22715.12    2500
54862  6760 0676003 22715.12    2500
54863  6760 0676004 22715.12    2500
52701 12019 1201901 21516.05    2500
52702 12019 1201902 21516.05    2500
48378 16474 1647401 17766.26    2500
48379 16474 1647402 17766.26    2500
47313 16753 1675301 12234.74    2500
55863 17261 1726101 17578.60    2500
55864 17261 1726102 17578.60    2500
55865 17261 1726103 17578.60    2500
55866 17261 1726104 17578.60    2500
55867 17261 1726105 17578.60    2500
55868 17261 1726106 17578.60    2500
23348 17520 1752001 23458.96    2500
23349 17520 1752002 23458.96    2500
23350 17520 1752003 23458.96    2500
23351 17520 1752004 23458.96    2500
37907 18552 1855201 12242.75    2500
14127 19861 1986101 28873.94    2500
38101 20247 2024701 17827.90    2500
47792 21898 2189801 19432.71    2500
4 samples of size 34 are set up
           id        region  eqIncome  .weight
848   1377102    Burgenland 13792.933  970.500
124   1419801    Burgenland 10069.840  970.500
12051 1764402 Lower Austria 19825.510 2225.400
5889  2084302 Lower Austria 35641.487 2225.400
4581  1518202 Lower Austria 13777.713 2225.400
12817 1332204 Lower Austria 22271.959 2225.400
11817 2383003 Lower Austria 31400.319 2225.400
16231 1359401        Vienna 33437.247 2331.400
19560 2193402        Vienna  8987.905 2331.400
14495 0684501        Vienna 15943.850 2331.400
13942 1020901        Vienna 22582.580 2331.400
24253 1229303        Vienna 20973.676 2331.400
27607 1834102     Carinthia 23515.616 1370.333
26458 1438703     Carinthia 27484.585 1370.333
28113 1119104     Carinthia 15084.129 1370.333
32191 2027002        Styria 11937.517 2035.500
29192 0862301        Styria 20915.180 2035.500
36787 0120801        Styria 13743.909 2035.500
30767 0328902        Styria 19158.700 2035.500
38670 1158902 Upper Austria 10548.640 2062.000
43978 1256502 Upper Austria 16259.120 2062.000
45116 1796702 Upper Austria 20633.990 2062.000
41191 0929302 Upper Austria 17255.994 2062.000
38451 0272201 Upper Austria 33015.413 2062.000
51307 0553802      Salzburg  8530.734 1341.667
50679 1871905      Salzburg 22256.032 1341.667
48756 0782301      Salzburg 13910.353 1341.667
52154 0052302         Tyrol  8306.500  959.200
53284 0274502         Tyrol 35249.120  959.200
53408 1651303         Tyrol 44624.300  959.200
51972 1341302         Tyrol  9911.427  959.200
52100 1214602         Tyrol  7874.813  959.200
57660 0281502    Vorarlberg 33374.481 1272.500
56527 1114102    Vorarlberg 38700.500 1272.500
4 samples are set up

The sample sizes are:
[1] 79 76 79 67
        hid      id        region  eqIncome   .weight
699   14709 1470901    Burgenland 38682.593  399.5000
700   14709 1470902    Burgenland 38682.593  399.5000
533   18149 1814901    Burgenland 11470.193  399.5000
534   18149 1814902    Burgenland 11470.193  399.5000
2312   2576 0257601 Lower Austria  8789.020  923.8000
11480  4356 0435601 Lower Austria  5962.886  923.8000
11481  4356 0435602 Lower Austria  5962.886  923.8000
11482  4356 0435603 Lower Austria  5962.886  923.8000
11483  4356 0435604 Lower Austria  5962.886  923.8000
11484  4356 0435605 Lower Austria  5962.886  923.8000
10791  8206 0820601 Lower Austria 16756.295  923.8000
10792  8206 0820602 Lower Austria 16756.295  923.8000
10793  8206 0820603 Lower Austria 16756.295  923.8000
10794  8206 0820604 Lower Austria 16756.295  923.8000
3052  10355 1035501 Lower Austria  8890.380  923.8000
8955  15306 1530601 Lower Austria 17140.824  923.8000
8956  15306 1530602 Lower Austria 17140.824  923.8000
8957  15306 1530603 Lower Austria 17140.824  923.8000
8958  15306 1530604 Lower Austria 17140.824  923.8000
13704  1100 0110001        Vienna 15783.840 1171.4000
16789  4723 0472301        Vienna 21222.780 1171.4000
16790  4723 0472302        Vienna 21222.780 1171.4000
16701  7343 0734301        Vienna 10985.847 1171.4000
16702  7343 0734302        Vienna 10985.847 1171.4000
15277 19097 1909701        Vienna 19555.910 1171.4000
19454 23740 2374001        Vienna 25573.844 1171.4000
19455 23740 2374002        Vienna 25573.844 1171.4000
19456 23740 2374003        Vienna 25573.844 1171.4000
25015  5541 0554101     Carinthia  9337.900  574.3333
25151  5546 0554601     Carinthia 18418.970  574.3333
27854  9312 0931201     Carinthia 19180.829  574.3333
27855  9312 0931202     Carinthia 19180.829  574.3333
27856  9312 0931203     Carinthia 19180.829  574.3333
27857  9312 0931204     Carinthia 19180.829  574.3333
30106  4316 0431601        Styria 17640.120  846.5000
30107  4316 0431602        Styria 17640.120  846.5000
31046  6281 0628101        Styria  8002.267  846.5000
31047  6281 0628102        Styria  8002.267  846.5000
29586 10153 1015301        Styria 10606.800  846.5000
28908 16619 1661901        Styria 16090.580  846.5000
41667   619 0061901 Upper Austria 26472.222  814.2000
41668   619 0061902 Upper Austria 26472.222  814.2000
41669   619 0061903 Upper Austria 26472.222  814.2000
37653  8995 0899501 Upper Austria 10231.330  814.2000
37602 14204 1420401 Upper Austria  8809.400  814.2000
39697 16921 1692101 Upper Austria 11493.213  814.2000
39698 16921 1692102 Upper Austria 11493.213  814.2000
37214 23989 2398901 Upper Austria  2935.070  814.2000
47560  8201 0820101      Salzburg  9897.610  557.0000
48502 16351 1635101      Salzburg 12465.747  557.0000
48503 16351 1635102      Salzburg 12465.747  557.0000
48542 22025 2202501      Salzburg 20132.767  557.0000
48543 22025 2202502      Salzburg 20132.767  557.0000
52727  1991 0199101         Tyrol  4940.987  377.8000
52728  1991 0199102         Tyrol  4940.987  377.8000
53574  3078 0307801         Tyrol 28626.755  377.8000
53575  3078 0307802         Tyrol 28626.755  377.8000
53576  3078 0307803         Tyrol 28626.755  377.8000
51522 10520 1052001         Tyrol 11166.180  377.8000
52687 11739 1173901         Tyrol 20082.700  377.8000
52688 11739 1173902         Tyrol 20082.700  377.8000
54952 16371 1637101         Tyrol 35377.960  377.8000
54953 16371 1637102         Tyrol 35377.960  377.8000
54954 16371 1637103         Tyrol 35377.960  377.8000
54955 16371 1637104         Tyrol 35377.960  377.8000
56238  8126 0812601    Vorarlberg 12080.200  492.5000
56365  9824 0982401    Vorarlberg 12132.820  492.5000

simFrame documentation built on May 30, 2017, 12:25 a.m.