[R] mlogit error

[gmacfarlane]

I actually have exactly the same question as Maha, and I wish that Z had
answered the question instead of providing a lesson in streamlined code
(valuable, but not helpful).

It seems as though mlogit.data repopulates the row.names field, and that
this is where the duplication comes in.

hbwtrips<-read.csv("workdata.csv",header=TRUE, sep=",",
dec=".",row.names="ROWS")

This works fine, and produces a table like the one below (but bigger). I can
run anything I want (descriptive statistics, aov, linear regression) from
the data.frame (so I know there are no duplicate row names in the source
table).

   HHID PERID CASE ALTNUM NUMALTS CHOSEN  IVTT  OVTT  TVTT   COST  DIST
WKZONE HMZONE RSPOPDEN RSEMPDEN WKPOPDEN
1     2     1    1      1       5      1 13.38  2.00 15.38  70.63  7.69   
664    726    15.52     9.96    37.26
2     2     1    1      2       5      0 18.38  2.00 20.38  35.32  7.69   
664    726    15.52     9.96    37.26
3     2     1    1      3       5      0 20.38  2.00 22.38  20.18  7.69   
664    726    15.52     9.96    37.26
4     2     1    1      4       5      0 25.90 15.20 41.10 115.64  7.69   
664    726    15.52     9.96    37.26
5     2     1    1      5       5      0 40.50  2.00 42.50   0.00  7.69   
664    726    15.52     9.96    37.26
6     3     1    2      1       5      0 29.92 10.00 39.92 390.81 11.62   
738      9    35.81    53.33    32.91
7     3     1    2      2       5      0 34.92 10.00 44.92 195.40 11.62   
738      9    35.81    53.33    32.91
8     3     1    2      3       5      0 21.92 10.00 31.92  97.97 11.62   
738      9    35.81    53.33    32.91
9     3     1    2      4       5      1 22.96 14.20 37.16 185.00 11.62   
738      9    35.81    53.33    32.91
10    3     1    2      5       5      0 58.95 10.00 68.95   0.00 11.62   
738      9    35.81    53.33    32.91
11    5     1    3      1       4      1  8.60  6.00 14.60  37.76  4.10   
696    667    85.35   105.93    29.45
12    5     1    3      2       4      0 13.60  6.00 19.60  18.88  4.10   
696    667    85.35   105.93    29.45
13    5     1    3      3       4      0 15.60  6.00 21.60  10.79  4.10   
696    667    85.35   105.93    29.45
14    5     1    3      4       4      0 16.87 21.40 38.27 105.00  4.10   
696    667    85.35   105.93    29.45
15    6     1    4      1       4      0 30.60  8.50 39.10 417.32 14.58   
665      8    32.31    25.61     0.00
16    6     1    4      2       4      0 35.70  8.50 44.20 208.66 14.58   
665      8    32.31    25.61     0.00
17    6     1    4      3       4      0 22.70  8.50 31.20 105.54 14.58   
665      8    32.31    25.61     0.00
18    6     1    4      4       4      1 24.27  9.00 33.27 193.49 14.58   
665      8    32.31    25.61     0.00
19    8     2    5      2       4      1 23.04  3.00 26.04  29.95  6.29   
679    704    33.04   106.52    89.24
20    8     2    5      3       4      0 25.04  3.00 28.04  17.12  6.29   
679    704    33.04   106.52    89.24
21    8     2    5      4       4      0 25.04 23.50 48.54 100.00  6.29   
679    704    33.04   106.52    89.24
22    8     2    5      5       4      0 34.35  3.00 37.35   0.00  6.29   
679    704    33.04   106.52    89.24
23    8     3    6      2       5      0 11.14  3.50 14.64  14.00  2.83   
679    665    33.04   106.52    32.31
24    8     3    6      3       5      0 13.14  3.50 16.64   8.00  2.83   
679    665    33.04   106.52    32.31
25    8     3    6      4       5      1  3.95 16.24 20.19 100.00  2.83   
679    665    33.04   106.52    32.31
26    8     3    6      5       5      0 16.05  3.50 19.55   0.00  2.83   
679    665    33.04   106.52    32.31
27    8     3    6      6       5      0  0.00  0.00 60.10   0.00  2.83   
679    665    33.04   106.52    32.31
28   12     2    7      1       6      1  8.80  3.00 11.80  31.65  3.44   
667    682    29.45    22.42     6.57
29   12     2    7      2       6      0 13.80  3.00 16.80  15.83  3.44   
667    682    29.45    22.42     6.57
30   12     2    7      3       6      0 15.80  3.00 18.80   9.04  3.44   
667    682    29.45    22.42     6.57


I then run 

> hbwmode<-mlogit.data(hbwtrips,varying=c(8:11),shape="long",
> choice="CHOSEN", alt.var="ALTNUM", row.names="ROWS")

which returns

Error in `row.names<-.data.frame`(`*tmp*`, value = c("1.1", "1.2", "1.3",  : 
  duplicate 'row.names' are not allowed
In addition: Warning message:
non-unique values when setting 'row.names': ‘1.1’, ‘10.1’, ‘10.4’, ‘100.4’,
‘1000.2’, ‘1001.1’, ‘1001.3’, ‘1002.2’, ‘1002.3’, ‘1003.4’, ‘1004.1’,
‘1004.2’, ‘1005.1’, ‘1005.3’, ‘1007.2’, ‘1008.3’, ‘1008.4’, ‘1009.1’,
‘1009.2’, ‘1009.3’, ‘101.1’, ‘1010.4’, ‘1011.1’, ‘1012.2’, ‘1013.3’,
‘1013.4’, ‘1015.1’, ‘1016.2’, ‘1018.3’, ‘1018.4’, ‘1019.1’, ‘1019.2’,
‘102.1’, ‘102.2’, ‘102.3’, ‘1020.3’, ‘1020.4’, ‘1021.1’, ‘1022.2’, ‘1022.3’,
‘1023.4’, ‘1024.1’, ‘1024.2’, ‘1025.3’, ‘1025.4’, ‘1026.5’, ‘1027.1’,
‘1027.2’, ‘1028.3’, ‘1029.1’, ‘1029.4’, ‘103.2’, ‘103.3’, ‘1030.2’,
‘1030.3’, ‘1031.1’, ‘1031.4’, ‘1032.2’, ‘1032.3’, ‘1033.1’, ‘1033.2’,
‘1034.3’, ‘1035.1’, ‘1035.2’, ‘1036.1’, ‘1036.3’, ‘1037.2’, ‘1037.3’,
‘1038.1’, ‘1 [... truncated] 

Did you ever find a real answer, Maha?

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