Hi,

Attempting to use the "anesrake" raking (also referred to as rim weighting)
package to weight survey data (Note: DATA is listed at the bottom along
with SESSION INFO AND COMMANDS ARGUMENTS USED to allow you to reproduce the
error). Presents following error message:

*"Error in selecthighestpcts(discrep1, inputter, pctlim) : *
*  No variables are off by more than 5 percent using the method you have
chosen, either weighting is unnecessary or a smaller pre-raking limit
should be chosen."*

However the sample proportions for the demographics are in fact far more
than 5% off the target proportions (see data below) no matter what
choosemethod argument is used. Have tried different "pctlim" settings as
well (even small ones such as 0.0001) and still get same message. Also
tried different "choosemethod" - both "max" and "total".

Tried to get help from the following but see nothing on this error in these
references:

*Package description at: cran.r-project.org/web/packages/anesrake/anesrake
.pdf*
*Paper by Josh Pasek:
http://www.stanford.edu/~jpasek/Josh_Pasek/Software_files/RakingDescription.pdf
*

Here is the* session info*:

> sessionInfo()
R version 2.14.0 (2011-10-31)
Platform: x86_64-pc-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_South Africa.1252  LC_CTYPE=English_South
Africa.1252
[3] LC_MONETARY=English_South Africa.1252 LC_NUMERIC=C

[5] LC_TIME=English_South Africa.1252

attached base packages:
[1] splines   stats     graphics  grDevices utils     datasets  methods
[8] base

other attached packages:
[1] anesrake_0.70    Hmisc_3.8-3      survival_2.36-10

loaded via a namespace (and not attached):
[1] cluster_1.14.1 grid_2.14.0    lattice_0.20-0


HERE ARE THE ARGUMENTS

> medufo <- read.csv("C:/Users/lenovo/Desktop/Medufo_weights/medufo.csv",
header = TRUE, row.names="ID")
> age <- c(25, 25, 28, 22)
> gender <- c(49, 51)
> ethnic <- c(58, 14, 5, 23)
> income <- c(1, 4, 7, 15, 18, 16, 19, 17, 1, 1,1)
> targets <- list(age, gender, ethnic, income)
> names(targets) <- c("age", "gender", "ethnic", "income")
> outsave <- anesrake(targets, medufo, caseid=1, verbose = TRUE)
> write.csv(print(outsave),
"C:/Users/lenovo/Desktop/Medufo_weights/outsave.csv")

HERE IS THE DATA LISTING

> list(medufo)
[[1]]
    age gender ethnic income
20    2      1      1      7
23    3      1      4      6
28    2      1      1     10
31    2      1      1      8
32    4      1      4      8
35    1      1      3      8
38    3      1      4      9
40    3      1      4      9
43    2      1      1      8
46    3      1      3      6
48    2      1      1      4
58    3      1      4      8
63    2      1      3      8
64    3      1      1      7
72    2      1      1      8
81    3      1      4      8
88    4      1      4      6
89    3      1      1      8
90    4      1      4      8
93    1      1      1      8
94    3      1      4      8
98    2      1      1      8
104   2      1      1     10
109   3      1      2      7
110   1      1      2      7
114   1      1      1      5
119   1      1      4      4
124   1      1      4      7
132   3      1      4      8
141   3      1      4     10
142   4      1      4      7
3     2      2      1     10
5     1      2      2      4
6     4      2      1      8
8     2      2      3      6
9     2      2      1      8
10    3      2      4      8
11    2      2      4      8
13    3      2      1      7
14    2      2      4      8
15    2      2      1      8
16    2      2      4      8
19    2      2      4      8
21    3      2      1      7
22    3      2      1      6
24    4      2      4      8
25    4      2      4      5
26    3      2      4      8
27    4      2      4      8
30    3      2      4     10
33    4      2      2      5
34    2      2      2      5
36    3      2      4      7
37    2      2      1      4
39    3      2      4      7
41    2      2      4      8
42    2      2      3      1
45    3      2      2      8
47    3      2      2      5
49    3      2      4      7
51    3      2      4      8
52    1      2      2      4
53    3      2      4      8
54    4      2      4      4
55    2      2      4     11
56    2      2      4      4
57    3      2      3      7
59    2      2      3      7
60    3      2      4      7
61    3      2      2      8
65    2      2      1      8
66    3      2      2      5
67    3      2      4      9
68    1      2      4      7
69    1      2      1      4
70    3      2      4      8
73    2      2      1      5
74    2      2      2      8
75    2      2      1      5
76    4      2      1      7
77    2      2      4      7
78    2      2      4      7
79    1      2      2      6
80    2      2      1      6
82    4      2      4      8
83    3      2      4      8
85    2      2      1      6
86    2      2      4      8
87    2      2      1      3
91    3      2      4      8
92    2      2      4      8
95    4      2      4      7
96    2      2      1      9
97    3      2      4      8
99    2      2      1      7
100   1      2      3      7
102   1      2      4      6
103   1      2      2      7
105   1      2      2      4
106   4      2      4      6
107   3      2      3      5
108   2      2      4      8
112   1      2      3      4
113   2      2      4      8
115   1      2      4      6
116   4      2      4      8
117   2      2      4      7
118   2      2      4      7
120   3      2      4     11
121   3      2      4      8
122   4      2      4      8
123   3      2      4      8
125   2      2      4      8
126   2      2      4      8
127   4      2      4      3
128   3      2      4      5
130   3      2      4      9
131   3      2      4      9
133   4      2      4      7
134   3      2      4      9
135   1      2      4      6
137   4      2      4      7
138   3      2      4      7
139   3      2      4      7
140   2      2      4     11
143   3      2      3     11
144   3      2      4      8
145   1      2      4      8
146   3      2      4      9
147   3      2      4      7
148   3      2      4      2
149   2      2      4      6

Thanks

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