[R] Odp: Loop overwrite and data output problems
RCulloch
ross.culloch at dur.ac.uk
Mon Mar 1 11:46:12 CET 2010
Hi Petr,
Thank you for your post - I really appreciate you taking the time over my
problem.
Apologies for not posting more data, it is just that the data set is rather
large, and I don't like posting the whole thing on the website for that
reason.
I have managed to random sample the 98 individuals so that I effectively get
98 data points from the data set, I do this with the script below, which I
appreciate may not be the best way to do it:
for (S in 1:1){
Sample.dat<-ALL.R[1,]
for (I in 1:98){
tmp<-ALL.R[ALL.R$ID2==I,]
max<-dim(tmp)[1]
if (I==1) Sample.dat[1,]<-tmp[sample(1:max,1),] else {
Sample.dat<-rbind(Sample.dat,tmp[sample(1:max,1),])
Here is the first section of the output for Sample.dat, some columns are not
used in the analysis and the majority of the variables are not shown here,
but what you can see is that the script has taken one data point from ID2
1:98 (columns are a bit skewed and ID2 appears under DAY because the numeric
for the rows is inc. in the e.g.)
SITE_NAME SITE YEAR NAME DAY ID2 n_DAY BEH_F BEH_T
1 NR 1 2007 A1 3 1 78 22 56
31 NR 1 2007 A2 1 2 24 1 23
80 NR 1 2007 D2 23 3 36 2 34
106 NR 1 2007 D5 19 4 34 9 25
136 NR 1 2007 E2 19 5 36 12 24
160 NR 1 2007 F10 13 6 48 4 44
193 NR 1 2007 F4 16 7 36 5 31
222 NR 1 2007 F8 15 8 47 8 39
263 NR 1 2007 G3 26 9 30 6 24
292 NR 1 2007 G4 25 10 30 8 22
317 NR 1 2007 G5 20 11 36 6 30
339 NR 1 2007 H1 12 12 42 11 31
370 NR 1 2007 I1 13 13 48 16 32
411 NR 1 2007 I4 24 14 12 2 10
433 NR 1 2007 J1 16 15 36 11 25
477 NR 1 2007 J2 30 16 36 1 35
500 NR 1 2007 K1 23 17 33 6 27
537 NR 1 2007 K4 30 18 36 4 32
567 NR 1 2007 L1 30 19 36 12 24
592 NR 1 2007 L2 25 20 30 9 21
614 NR 1 2007 M2 17 21 36 4 32
644 NR 1 2007 M3 17 22 24 4 20
688 NR 1 2007 M4 31 23 36 3 33
707 NR 1 2007 N1 20 24 36 4 32
741 NR 1 2007 N4 24 25 1 0 1
776 NR 1 2007 P1 29 26 36 10 26
804 NR 1 2007 R1 27 27 18 0 18
836 NR 1 2007 R4 29 28 36 3 33
862 NR 1 2007 S1 25 29 30 11 19
897 NR 1 2007 S4 30 30 36 3 33
911 NR 1 2008 A1 11 31 110 24 86
930 NR 1 2008 A2 3 32 114 34 80
1159 NR 1 2008 A3 16 33 115 19 96
1178 NR 1 2008 A4 8 34 121 29 92
1205 NR 1 2008 A5 8 35 62 19 43
1246 NR 1 2008 B1 22 36 105 39 66
1258 NR 1 2008 C1 7 37 49 12 37
1289 NR 1 2008 C3 11 38 121 40 81
1328 NR 1 2008 D1 23 39 35 12 23
1354 NR 1 2008 F1 22 40 109 31 78
1377 NR 1 2008 G1 18 41 111 20 91
1400 NR 1 2008 G2 14 42 115 15 100
978 NR 1 2008 H1 24 43 91 23 68
1438 NR 1 2008 H2 25 44 91 18 73
1003 NR 1 2008 I1 22 45 109 28 81
1452 NR 1 2008 I2 12 46 30 11 19
1491 NR 1 2008 I3 24 47 91 24 67
1025 NR 1 2008 I4 17 48 34 9 25
1059 NR 1 2008 J1 24 49 91 16 75
1512 NR 1 2008 J3 18 50 92 21 71
1535 NR 1 2008 J4 14 51 44 2 42
1564 NR 1 2008 J6 16 52 115 13 102
1080 NR 1 2008 K1 18 53 111 4 107
1595 NR 1 2008 K2 20 54 41 12 29
1620 NR 1 2008 K3 18 55 27 7 20
1104 NR 1 2008 L2 15 56 48 9 39
1650 NR 1 2008 L4 21 57 115 33 82
1677 NR 1 2008 L5 21 58 111 24 87
1143 NR 1 2008 N1 28 59 75 24 51
1701 NR 1 2008 N3 18 60 107 18 89
1735 NR 1 2008 NNB 25 61 91 11 80
1757 NR 1 2008 O1 20 62 20 9 11
2002 FA 0 2008 A10 8 63 95 28 67
2006 FA 0 2008 A11 2 64 46 14 32
2020 FA 0 2008 A12 6 65 97 30 67
2026 FA 0 2008 A13 2 66 88 33 55
2038 FA 0 2008 A14 4 67 97 32 65
2049 FA 0 2008 A15 5 68 92 34 58
2055 FA 0 2008 A16 1 69 20 5 15
1888 FA 0 2008 A2 4 70 97 28 69
1916 FA 0 2008 A3 2 71 88 19 69
1929 FA 0 2008 A4 5 72 91 28 63
1937 FA 0 2008 A5 3 73 97 30 67
2069 FA 0 2008 A6 5 74 91 18 73
2082 FA 0 2008 A7 8 75 95 17 78
2085 FA 0 2008 A8 1 76 82 13 69
2098 FA 0 2008 A9 4 77 97 29 68
1947 FA 0 2008 B1 3 78 97 18 79
1987 FA 0 2008 B2 3 79 97 24 73
1958 FA 0 2008 C1 4 80 96 22 74
2114 FA 0 2008 C2 10 81 91 17 74
1973 FA 0 2008 D1 9 82 97 34 63
1904 FA 0 2008 D2 10 83 48 20 28
2124 FA 0 2008 E1 10 84 91 20 71
1910 FA 0 2008 E2 6 85 31 13 18
1983 FA 0 2008 F1 9 86 97 20 77
1765 FA 0 2007 A1 1 87 30 11 19
1778 FA 0 2007 B1 4 88 36 20 16
1808 FA 0 2007 B13 4 89 36 25 11
1821 FA 0 2007 B2 7 90 33 8 25
1834 FA 0 2007 B3 10 91 15 3 12
1841 FA 0 2007 B4 7 92 35 11 24
1845 FA 0 2007 B6 1 93 30 8 22
1864 FA 0 2007 B7 10 94 9 4 5
1874 FA 0 2007 B8 10 95 18 4 14
1878 FA 0 2007 B9 4 96 36 14 22
1793 FA 0 2007 C1 9 97 36 5 31
1799 FA 0 2007 G1 5 98 36 5 31
I then run the random sample of data through a model then using the MuMIn
package and the dredge command I get a list of all of the possible subsets
of the model in order of lowest to highest AIC values, the script below is
shown for that:
m1.R<-glm(cbind(Sample.dat$BEH_T, Sample.dat$BEH_F) ~ Sample.dat$SITE +
Sample.dat$YEAR + Sample.dat$PRECIP_MM_DAY + Sample.dat$PUP_AGE_EST +
Sample.dat$MO_AIR_TEMP, family="binomial")
mod<-dredge(m1.R)
The problem occurs here, manually I can do this fine, but for a 100 or so
simulations you don't want to do it manually. So I want to take mod[1,] for
each simulation and store that to look at later, but any way in which I try
to do this results in the data being overwritten.
I'm not sure if this is any clear, I am sorry, It is taking me a little
longer to get my head around looping scripts!
Best wishes,
Ross
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