[R] Sampling in R
Uwe Ligges
ligges at statistik.tu-dortmund.de
Tue Apr 21 13:07:16 CEST 2009
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 50000 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,
> 0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.1333333,0.1818182,0.1702128,
> 0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.4666667,0.4464286,0.362069,0.4285714,0.4561404,
> 0.4736842,0.4545455,0.4166667,0.4181818,0.4590164,0.5166667,0.5423729,0.4833333,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
> 0.5166667,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.4583333,0.3877551,0.4375,0.4117647,0.4313725,0.5333333,0.3962264,
> 0.3548387,0.5272727,0.4137931,0.3928571,0.4666667,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.4333333,0.4,0.4285714,
> 0.4516129,0.5090909,0.4464286,0.4642857,0.4166667,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
> 0.5925926,0.5769231,0.5818182,0.4444444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
> 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(0.2553191,0.4107143,0.5660377,0.3888889,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
> 0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.1166667,0.1785714,
> 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,
> 0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.4722222,0.5,0.3521127,0.4393939,0.3787879,
> 0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.3666667,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
> 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,
> 0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.3666667,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
> 0.4821429,0.5,0.557377,0.4333333,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
>
> my.cor<-cor(Xvar, Yvar)
> print(my.cor)
>
> nperm<-49999
> 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.cor>0) Perm.Cor.Sorted<-sort(Perm.Cor, decreasing=TRUE)
> if(mat.cor<0) 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, 3
data points ...
Uwe Ligges
> Kind Regards
>
> Seyit Ali
>
>
> ------------------------------------------------------------------------------------------------------------------
> Dr. Seyit Ali KAYIS
> Selcuk University
> Faculty of Agriculture
> Kampus, Konya, TURKEY
>
> s_a_kayis at yahoo.com, s_a_kayis at 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/
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