I only include 12 variables in for tuples command, why the observation numbers are out of range? Should't More than 2 billion observations be allowed?
Here is the sample code and data, could anyone explain this? Thanks a lot!
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(c1 c2 c3) byte(c4 c5) float c6 byte(c7 c8 c9 c10) float c11 double y float x int id
.4201681 3.296207 14.13587 0 0 3.8728664 2 2 44 2 3.178054 54 0 1
.4201681 3.296207 14.13587 0 0 3.8728664 2 1 59 2 3.178054 76 0 1
.4201681 3.296207 14.13587 0 0 3.8728664 2 2 43 2 3.178054 68.5 0 1
.4201681 3.296207 14.13587 0 0 3.8728664 2 1 43 2 3.178054 49 0 1
.4201681 3.296207 14.13587 0 0 3.8728664 2 1 48 2 3.178054 76 0 1
.6 5.588671 . 0 0 3.8728664 2 2 33 2 3.0445225 56 0 2
.6 5.588671 . 0 0 3.8728664 2 1 58 2 3.0445225 72 0 2
.6 5.588671 . 0 0 3.8728664 2 1 57 2 3.0445225 54 0 2
.6 5.588671 . 0 0 3.8728664 2 1 54 2 3.0445225 75 1 2
.6 5.588671 . 0 0 3.8728664 2 2 35 2 3.0445225 54 0 2
1 6.269854 39.35821 1 0 7.760126 2 2 38 1 3.713572 81 0 4
1 6.269854 39.35821 1 0 7.760126 2 1 43 1 3.713572 73 0 4
1 6.269854 39.35821 1 0 7.760126 2 1 43 1 3.713572 80 0 4
1 6.269854 39.35821 1 0 7.760126 2 2 43 1 3.713572 82 0 4
1 6.269854 39.35821 1 0 7.760126 2 1 33 1 3.713572 78 0 4
.95 4.5217886 .29449838 0 0 5.648974 2 1 60 5 3.0445225 47 0 11
.95 4.5217886 .29449838 0 0 5.648974 2 1 47 5 3.0445225 55 0 11
.95 4.5217886 .29449838 0 0 5.648974 2 2 34 5 3.0445225 47 0 11
.95 4.5217886 .29449838 0 0 5.648974 2 1 53 5 3.0445225 52 0 11
.95 4.5217886 .29449838 0 0 5.648974 2 2 39 5 3.0445225 47 0 11
.8333333 5.56452 52 0 0 5.080659 2 2 38 3 2.944439 65 0 13
.8333333 5.56452 52 0 0 5.080659 2 2 41 3 2.944439 80 0 13
.8333333 5.56452 52 0 0 5.080659 2 1 48 3 2.944439 64 0 13
.8333333 5.56452 52 0 0 5.080659 2 1 54 3 2.944439 76 0 13
.8333333 5.56452 52 0 0 5.080659 2 1 40 3 2.944439 76 0 13
1 4.574711 2.1333334 0 0 3.8728664 2 1 54 1 2.1972246 85 0 24
1 4.574711 2.1333334 0 0 3.8728664 2 2 42 1 2.1972246 68 0 24
1 4.574711 2.1333334 0 0 3.8728664 2 1 55 1 2.1972246 83 0 24
1 4.574711 2.1333334 0 0 3.8728664 2 2 38 1 2.1972246 72 0 24
1 4.574711 2.1333334 0 0 3.8728664 2 1 54 1 2.1972246 72 0 24
.7735849 6.294971 .4524722 0 0 8.326396 2 1 60 1 3.988984 81 0 25
.7735849 6.294971 .4524722 0 0 8.326396 2 1 37 1 3.988984 65 0 25
.7735849 6.294971 .4524722 0 0 8.326396 2 1 48 1 3.988984 57 0 25
.7735849 6.294971 .4524722 0 0 8.326396 2 2 46 1 3.988984 75 0 25
.7735849 6.294971 .4524722 0 0 8.326396 2 2 36 1 3.988984 73 0 25
1 4.348082 .18771826 0 0 5.559103 2 2 34 3 2.833213 62 0 29
1 4.348082 .18771826 0 0 5.559103 2 1 41 3 2.833213 62 0 29
1 4.348082 .18771826 0 0 5.559103 2 1 37 3 2.833213 59 0 29
1 4.348082 .18771826 0 0 5.559103 2 2 54 3 2.833213 65 0 29
1 4.348082 .18771826 0 0 5.559103 2 1 43 3 2.833213 47 0 29
.7619048 4.1311584 10.36379 0 0 7.27337 2 2 33 3 3.0910425 70 0 30
.7619048 4.1311584 10.36379 0 0 7.27337 2 1 57 3 3.0910425 87 0 30
.7619048 4.1311584 10.36379 0 0 7.27337 2 1 55 3 3.0910425 87 0 30
.7619048 4.1311584 10.36379 0 0 7.27337 2 2 55 3 3.0910425 62 0 30
.7619048 4.1311584 10.36379 0 0 7.27337 2 1 60 3 3.0910425 80 0 30
1 3.851211 1.0779494 0 0 7.251749 1 2 57 1 2.772589 69 0 31
1 3.851211 1.0779494 0 0 7.251749 1 2 39 1 2.772589 72 1 31
1 3.851211 1.0779494 0 0 7.251749 1 1 53 1 2.772589 66 0 31
1 3.851211 1.0779494 0 0 7.251749 1 1 60 1 2.772589 63 0 31
1 3.851211 1.0779494 0 0 7.251749 1 1 49 1 2.772589 74 0 31
.7027027 6.02369 .40595105 0 1 7.302857 2 2 41 2 3.637586 70 0 37
.7027027 6.02369 .40595105 0 1 7.302857 2 1 47 2 3.637586 65 0 37
.7027027 6.02369 .40595105 0 1 7.302857 2 1 41 2 3.637586 81 0 37
.7027027 6.02369 .40595105 0 1 7.302857 2 1 60 2 3.637586 74 0 37
.7027027 6.02369 .40595105 0 1 7.302857 2 2 41 2 3.637586 74 0 37
.6969697 4.927254 .32009345 0 1 7.199678 2 1 57 3 3.5263605 82 0 38
.6969697 4.927254 .32009345 0 1 7.199678 2 2 33 3 3.5263605 77 0 38
.6969697 4.927254 .32009345 0 1 7.199678 2 1 55 3 3.5263605 84 0 38
.6969697 4.927254 .32009345 0 1 7.199678 2 1 60 3 3.5263605 85 0 38
.6969697 4.927254 .32009345 0 1 7.199678 2 2 55 3 3.5263605 75 0 38
1 5.25942 .7263445 0 1 8.163983 1 1 43 4 3.367296 47 0 39
1 5.25942 .7263445 0 1 8.163983 1 1 45 4 3.367296 55 1 39
1 5.25942 .7263445 0 1 8.163983 1 2 38 4 3.367296 53 0 39
1 5.25942 .7263445 0 1 8.163983 1 1 38 4 3.367296 62 0 39
1 5.25942 .7263445 0 1 8.163983 1 2 43 4 3.367296 67 0 39
1 5.204007 2.397351 0 0 8.326396 1 1 44 4 3.0445225 47 1 41
1 5.204007 2.397351 0 0 8.326396 1 2 45 4 3.0445225 60 1 41
1 5.204007 2.397351 0 0 8.326396 1 2 43 4 3.0445225 76 0 41
1 5.204007 2.397351 0 0 8.326396 1 1 57 4 3.0445225 87 0 41
1 5.204007 2.397351 0 0 8.326396 1 1 42 4 3.0445225 47 0 41
.72 6.396729 1.7342253 1 0 6.976133 4 2 44 3 3.2580965 81 0 42
.72 6.396729 1.7342253 1 0 6.976133 4 2 39 3 3.2580965 87 0 42
.72 6.396729 1.7342253 1 0 6.976133 4 1 33 3 3.2580965 54 0 42
.72 6.396729 1.7342253 1 0 6.976133 4 1 44 3 3.2580965 80 0 42
.72 6.396729 1.7342253 1 0 6.976133 4 1 54 3 3.2580965 78 0 42
1 5.187944 18.360825 0 0 6.264597 4 2 33 4 2.6390574 76 0 44
1 5.187944 18.360825 0 0 6.264597 4 1 56 4 2.6390574 75 0 44
1 5.187944 18.360825 0 0 6.264597 4 1 51 4 2.6390574 67 0 44
1 5.187944 18.360825 0 0 6.264597 4 2 33 4 2.6390574 70 0 44
1 5.187944 18.360825 0 0 6.264597 4 1 48 4 2.6390574 77 0 44
.4347826 5.617498 .53189015 0 0 6.13027 4 2 47 2 3.178054 72 0 45
.4347826 5.617498 .53189015 0 0 6.13027 4 2 46 2 3.178054 68 0 45
.4347826 5.617498 .53189015 0 0 6.13027 4 1 60 2 3.178054 73 0 45
.4347826 5.617498 .53189015 0 0 6.13027 4 1 60 2 3.178054 87 0 45
.4347826 5.617498 .53189015 0 0 6.13027 4 1 46 2 3.178054 84 0 45
.76 5.056246 .1625 0 0 7.036149 2 2 47 5 3.2580965 55 1 46
.76 5.056246 .1625 0 0 7.036149 2 1 34 5 3.2580965 49 1 46
.76 5.056246 .1625 0 0 7.036149 2 1 59 5 3.2580965 47 1 46
.76 5.056246 .1625 0 0 7.036149 2 2 44 5 3.2580965 68 0 46
.76 5.056246 .1625 0 0 7.036149 2 1 58 5 3.2580965 47 0 46
1 4.684628 .8477162 0 0 6.322296 2 1 35 2 2.772589 58 0 50
1 4.684628 .8477162 0 0 6.322296 2 2 33 2 2.772589 72 0 50
1 4.684628 .8477162 0 0 6.322296 2 1 51 2 2.772589 78 0 50
1 4.684628 .8477162 0 0 6.322296 2 1 49 2 2.772589 77 0 50
1 4.684628 .8477162 0 0 6.322296 2 2 43 2 2.772589 64 0 50
1 5.966865 .4755262 1 0 6.678329 4 2 43 5 3.178054 80 0 51
1 5.966865 .4755262 1 0 6.678329 4 1 43 5 3.178054 75 0 51
1 5.966865 .4755262 1 0 6.678329 4 2 38 5 3.178054 72 0 51
1 5.966865 .4755262 1 0 6.678329 4 1 43 5 3.178054 77 0 51
1 5.966865 .4755262 1 0 6.678329 4 1 33 5 3.178054 62 0 51
end
cap drop pvalue IV
cap drop pvalueMin numOfIV
generate pvalue = .
generate IV = ""
tuples c1 c2 c3 c4 c5 c6 c7 c8 c9 c10 c11
quietly forvalues i = 1/`ntuples' {
replace IV = "`tuple`i''" in `i'
reg y i.x `tuple`i'' ,vce(cluster id )
replace pvalue = el(r(table),4,1) in `i'
}
dis `ntuples'
0 Response to about tuples:why observation numbers are out of range ? It should't be
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