[R] read in data file into R

[Benedikt Gehr]

Hi
I'm trying to read a data file with output from another program (admb) 
into R for further analysis. However I'm not very successfull. The file 
extension for the data file is file.rep but it also doesn't help when I 
change it to file.txt

I have two problems/questions:

1.  The file is a single line of n values separated by a single space 
tab each. These values represent a time series of length n. How can I 
make a numeric vector with this data?
When I use the "read.table" command and read in the file R produces a 
list of as many objects as there are values (n). However what I need is 
a vector of length n in order to work with the data. When I try to 
coerce the list into a single vector using "as.vector" this doesn't work.
When I specify sep="\n" then I get a list where all the n values are 
treated as one value and I cant extract single values.

2. And related to the issue above: When I have a data file which 
consists of two objects, one is a matrix and the other one is a vector. 
Can I read the file into R all at once as a list with 2 objects and then 
extract the matrix and the vector and work with them? Or is it necessary 
to first make two files, for each object one?

Below I have copied a subset of my data files for ilustration. This 
seems a very silly question but I just didn't manage to to it.
Thanks a lot for the help

cheers

beni

This is a subset of my data file for 1.:

Time series of reconstructed populations
 3709.17 2660.93 2045.36 2090.33 2096.93 2205.65 2083.72 1797.53 1884.61 
1946.59 2101.66 2220.03 2080.04 2097.07 2332.9 2325.47 2091.67 2091.54 
2072.38 2025.31 1919.54 1781.95 1867.96 1685.12 1826.31 1654.25 1593.84 
1430.96 1539.89 1587.35 1472.32 1737.02 1510.37 1570.15 1723.21 1755.3 
1843.85 1829.2 1880.63 1916.79 1945.86 2096.64 2246.67 2101.16 2134.39 
2018.1 2174.04 ....

This is a subset of the data file for 2.:
Reconstructed population
 203.026 200.005 205.206 217.36 279.415 750.965
 495.041 91.3615 162.004 147.748 156.499 492.444
 463.284 222.768 74.0028 116.643 106.379 303.677
 468.042 208.478 180.442 53.282 83.9828 194.375
 460.216 210.619 168.867 129.918 38.3631 135.857
 461.88 207.097 170.601 121.584 93.5413 80.3142
 474.857 207.846 167.749 122.833 87.5406 98.5
 479.117 213.686 168.355 120.779 88.4396 101.233
 480.269 215.603 173.085 121.216 86.961 102.94
 483.206 216.121 174.638 124.622 87.2753 102.538
 486.657 217.443 175.058 125.739 89.7275 102.608
 490.516 218.996 176.128 126.042 90.5324 104.401
 494.019 220.732 177.386 126.813 90.7501 105.676
 497.345 222.308 178.793 127.718 91.305 106.327
 500.797 223.805 180.07 128.731 91.9571 106.979
 504.331 225.359 181.282 129.65 92.6863 107.701
 507.892 226.949 182.54 130.523 93.3482 108.507
 511.458 228.551 183.829 131.429 93.9768 109.296
 515.039 230.156 185.127 132.357 94.629 110.054
 518.65 231.767 186.426 133.291 95.2967 110.818
 522.291 233.393 187.732 134.227 95.9696 111.595
 525.957 235.031 189.048 135.167 96.6434 112.381
 529.648 236.681 190.375 136.115 97.32 113.171
 533.364 238.342 191.711 137.07 98.0025 113.964
 537.106 240.014 193.057 138.032 98.6905 114.763
 541.61 241.698 194.411 139.001 99.3832 115.569
 545.435 243.725 195.775 139.976 100.081 116.38
 549.312 245.446 197.417 140.958 100.783 117.197
 553.294 247.19 198.811 142.14 101.49 118.019
 557.349 248.982 200.224 143.144 102.341 118.847

time series of the reconstructed population
 1855.98 1545.1 1286.75 1188.6 1143.84 1135.02 1159.33 1171.61 1180.07 
1188.4 1197.23 1206.61 1215.38 1223.8 1232.34 1241.01 1249.76 1258.54 
1267.36 1276.25 1285.21 1294.23 1303.31 1312.45 1321.66 1331.67 1341.37 
1351.11 1360.94 1370.89