data.examples {EVER} | R Documentation |
Example data frames and functions. Allow to run R code contained in the 'Examples' section of the EVER package help pages.
data(data.examples)
The main data frame, named example
, contains (artificial) data from a two stage stratified cluster sampling design. The sample is made up of 3000 final units, for which the following 21 variables were observed:
towcod
numeric
famcod
numeric
key
numeric
weight
numeric
stratum
factor
with levels 801
802
803
901
902
903
904
905
906
907
908
1001
1002
1003
1004
1005
1006
1007
1008
1009
1101
1102
1103
1104
3001
3002
3003
3004
3005
3006
3007
3008
3009
3010
3011
3012
3101
3102
3103
3104
3105
3106
3107
3108
3201
3202
3203
3204
5401
5402
5403
5404
5405
5406
5407
5408
5409
5410
5411
5412
5413
5414
5415
5416
5501
5502
5503
5504
9301
9302
9303
9304
9305
9306
9307
9308
9309
9310
9311
9312
SUPERSTRATUM
factor
with levels 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
sr
integer
with values 0
(NSR strata) and 1
(SR strata)regcod
factor
with levels 6
7
10
procod
factor
with levels 8
9
10
11
30
31
32
54
55
93
x1
numeric
x2
numeric
x3
numeric
y1
numeric
y2
numeric
y3
numeric
age5c
factor
with levels 1
2
3
4
5
age10c
factor
with levels 1
2
3
4
5
6
7
8
9
10
sex
factor
with levels f
m
marstat
factor
with levels married
unmarried
widowed
z
numeric
income
numeric
Objects pop01
, ..., pop05p
contain known population totals for various calibration models. Object pairs with names differing in the 'p
' suffix (such as pop03
and pop03p
) refer to the same calibration problem but pertain to different solution methods (global and iterative respectively, see kottcalibrate
). The two-component numeric vector bounds
expresses a possible choice for the allowed range for the ratios between calibrated weights and direct weights in the aforementioned calibration problems.
Functions ones
, poverty
and ratio
are intended to show how to use kottby.user
for calculating estimates, standard errors and confidence intervals for user-defined estimators.
data(data.examples)