[R] Sampling in R
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[R] Sampling in R
__ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Sampling in R
(Sorry for multiple posting. Seems to be my msg is not distributed in my
previous emails)
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my
original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are
in the attached file. I want to understand where I am making a mistake. Any
comment is deeply appreciated.
Kind Regards
Seyit Ali
Xvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor-cor(XvarNew, YvarNew)
Perm.Cor-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted-sort(Xvar, decreasing=TRUE)
YvarSorted-sort(Yvar, decreasing=TRUE)
max.cor-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=TRUE)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=FALSE)
T95-Perm.Cor.Sorted[(nperm+1)*0.05]# 95% treshold value
T99-Perm.Cor.Sorted[(nperm+1)*0.01]# 99% treshold value
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R-help@r-project.org mailing list
https
[R] Sampling in R: Please read my email from attached text.
(Sorry for multiple posting. Seems to be my msg is not distributed in my
previous emails)
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my
original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are
in the attached file. I want to understand where I am making a mistake. Any
comment is deeply appreciated.
Kind Regards
Seyit Ali
Xvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor-cor(XvarNew, YvarNew)
Perm.Cor-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted-sort(Xvar, decreasing=TRUE)
YvarSorted-sort(Yvar, decreasing=TRUE)
max.cor-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=TRUE)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=FALSE)
T95-Perm.Cor.Sorted[(nperm+1)*0.05]# 95% treshold value
T99-Perm.Cor.Sorted[(nperm+1)*0.01]# 99% treshold value
__
R-help@r-project.org mailing list
https
[R] Sampling in R
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my
original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are below
Xvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor-cor(XvarNew, YvarNew)
Perm.Cor-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted-sort(Xvar, decreasing=TRUE)
YvarSorted-sort(Yvar, decreasing=TRUE)
max.cor-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=TRUE)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=FALSE)
T95-Perm.Cor.Sorted[(nperm+1)*0.05]# 95% treshold value
T99-Perm.Cor.Sorted[(nperm+1)*0.01]# 99% treshold value
I want to understand where I am making a mistake. Any comment is deeply
appreciated.
Kind Regards
Seyit Ali
--
Dr. Seyit Ali KAYIS
Selcuk University
Faculty of Agriculture
Kampus, Konya, TURKEY
[R] Sampling in R
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my
original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are
in the attached file. I want to understand where I am making a mistake. Any
comment is deeply appreciated.
Kind Regards
Seyit Ali
--
Dr. Seyit Ali KAYIS
Selcuk University
Faculty of Agriculture
Kampus, Konya, TURKEY
s_a_ka...@yahoo.com,s_a_ka...@hotmail.com
Tell: +90 332 223 2830 Mobile: +90 535 587 1139 Fax: +90 332 241 0108
Greetings from Konya, TURKEY
http://www.ziraat.selcuk.edu.tr/skayis/
--
_
No-one wants to be lonely this Autumn Find someone to snuggle up with
Fchannel%2Findex%2Easpx%3Ftrackingid%3D1048628_t=773568480_r=nzWINDOWSliveMAILemailTAGLINES_m=EXTXvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar
Re: [R] Sampling in R
When you shuffle the observations independently, you are performing a
permutation test (though for this you only need to shuffle one side of
the pairs). When you sort the observations you are doing something
ridiculous that has no statistical meaning that I know.
I'm not very familiar with bootstrap CI's, but I think the idea is to
sample the PAIRS of data WITH replacement:
http://lmgtfy.com/?q=bootstrap+correlation
(first link is to a good overview by David Howell)
On Tue, Apr 21, 2009 at 7:25 AM, Seyit Ali Kayis s_a_ka...@hotmail.com wrote:
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for
my original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are below
Xvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor-cor(XvarNew, YvarNew)
Perm.Cor-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted-sort(Xvar, decreasing=TRUE)
YvarSorted-sort(Yvar, decreasing=TRUE)
max.cor-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor0) Perm.Cor.Sorted
Re: [R] Sampling in R: Please read my email from attached text.
You need to sample pairs rather than sampling individually within Xvar and Yvar. You also generally sample with replacement. If you sample without replacement for the length of the data, then you just get the same set. On Apr 21, 2009, at 3:54 AM, skayis selcuk wrote: Data_and_Sampling_codes.txt David Winsemius, MD Heritage Laboratories West Hartford, CT __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Sampling in R
Dear Seyit,
You might consider the boot package in this situation. Here is an example:
require(boot)
DF-data.frame(Xvar,Yvar)
temp - boot(DF, function(DF,d){
S - DF[d,]
cor(S$Xvar,S$Yvar)
},
R = 5000)
temp$t0
# [1] 0.617422
max(temp$t)
# [1] 0.7783784
hist(temp$t)
Once you load the boot package, take a look at ?boot.
HTH,
Jorge
On Tue, Apr 21, 2009 at 4:53 AM, Seyit Ali Kayis s_a_ka...@hotmail.comwrote:
Dear R users,
I need to do sampling without replacement (bootstraps). I have two
variables (Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and
getting 95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of
my original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my
Xvar and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation
for my original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and
codes for the scenario above are
in the attached file. I want to understand where I am making a mistake. Any
comment is deeply appreciated.
Kind Regards
Seyit Ali
--
Dr. Seyit Ali KAYIS
Selcuk University
Faculty of Agriculture
Kampus, Konya, TURKEY
s_a_ka...@yahoo.com,s_a_ka...@hotmail.com
Tell: +90 332 223 2830 Mobile: +90 535 587 1139 Fax: +90 332 241 0108
Greetings from Konya, TURKEY
http://www.ziraat.selcuk.edu.tr/skayis/
--
_
No-one wants to be lonely this Autumn Find someone to snuggle up with
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__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Sampling in R
Seyit Ali Kayis wrote:
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables (Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting 95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my original data).
I repeated the sampling a couple of time and none of them produced a correlation
coefficient higher than my original data set. However, if I sort out my Xvar and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my original data.
I am doing sampling in another program and getting at least 1% higher correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes for the scenario above are below
Xvar-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor-cor(Xvar, Yvar)
print(my.cor)
nperm-4
Perm.Cor-NULL
for (iperm in 1:nperm) {
XvarNew-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor-cor(XvarNew, YvarNew)
Perm.Cor-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted-sort(Xvar, decreasing=TRUE)
YvarSorted-sort(Yvar, decreasing=TRUE)
max.cor-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=TRUE)
if(mat.cor0) Perm.Cor.Sorted-sort(Perm.Cor, decreasing=FALSE)
T95-Perm.Cor.Sorted[(nperm+1)*0.05]# 95% treshold value
T99-Perm.Cor.Sorted[(nperm+1)*0.01]# 99% treshold value
I want to understand where I am making a mistake. Any comment is deeply
appreciated.
Well, if you are permuting Xvar and Yvar separately or sorting them
(separately), then you cannot expect to get the same correlation again.
Look at the formula and make an example for yourself with just, say
