R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(126.64
+ ,126.81
+ ,125.84
+ ,126.77
+ ,124.34
+ ,124.4
+ ,120.48
+ ,118.54
+ ,117.66
+ ,116.97
+ ,120.11
+ ,119.16
+ ,116.9
+ ,116.11
+ ,114.98
+ ,113.65
+ ,115.82
+ ,117.59
+ ,118.57
+ ,118.07
+ ,114.98
+ ,114.04
+ ,115.02
+ ,114.28
+ ,115.04
+ ,116.7
+ ,119.21
+ ,118.39
+ ,116.5
+ ,115.46
+ ,117.59
+ ,117.33
+ ,116.2
+ ,116.83
+ ,118.99
+ ,118.62
+ ,121.09
+ ,122.4
+ ,123.76
+ ,125.33
+ ,123.23
+ ,122.52
+ ,123.64
+ ,124.67
+ ,124.71
+ ,122.53
+ ,124.4
+ ,125.45
+ ,125.35
+ ,124.3
+ ,127.03
+ ,128.51
+ ,128.1
+ ,128.94
+ ,129.67
+ ,129.87
+ ,131.12
+ ,132.68
+ ,132.24
+ ,133.63
+ ,129.91
+ ,127.93
+ ,131.17
+ ,130.86
+ ,133.48
+ ,134.08
+ ,136.02
+ ,132.8
+ ,132.37
+ ,133.05
+ ,132.57
+ ,130.7
+ ,130.5
+ ,129.67
+ ,127.8
+ ,126.82
+ ,126.85
+ ,128.28
+ ,128.3
+ ,126.82
+ ,125.08
+ ,128.53
+ ,130.34
+ ,131.52
+ ,132.59
+ ,131.17
+ ,132.72
+ ,133.36
+ ,132.82
+ ,132.9
+ ,130.9
+ ,129.41
+ ,128.67
+ ,129.28
+ ,130.91
+ ,131.06
+ ,130.84
+ ,131.41
+ ,133.22
+ ,132.06
+ ,132.48
+ ,134.38
+ ,135.22
+ ,134.89
+ ,136.09
+ ,136.33
+ ,136.32
+ ,137.48
+ ,136.53
+ ,136.8
+ ,138.03
+ ,137.39
+ ,137.55
+ ,136.08
+ ,134.78
+ ,133.28
+ ,133.57
+ ,134.84
+ ,133.02
+ ,133.49
+ ,133.77
+ ,134.34
+ ,134.5
+ ,134.03
+ ,135.51
+ ,136.53
+ ,135.95
+ ,134.32
+ ,132.44
+ ,133.61
+ ,131.02
+ ,130.05
+ ,128.21
+ ,129.03
+ ,130.34
+ ,131.57
+ ,132.63
+ ,132.06
+ ,134.44
+ ,134.1
+ ,132.49
+ ,134.23
+ ,134.92
+ ,135.61
+ ,134.53
+ ,133.86
+ ,133.89
+ ,135.33
+ ,135.86
+ ,136.22
+ ,137.38
+ ,137.31
+ ,136.89
+ ,138.01
+ ,136.72
+ ,135.77
+ ,137.52
+ ,135.61
+ ,132.94
+ ,134.12
+ ,132.55
+ ,134.11
+ ,134.19
+ ,135.57
+ ,135.05
+ ,134.32
+ ,133.61
+ ,134.75
+ ,133.1
+ ,133.26
+ ,131.63
+ ,132.47
+ ,132.45
+ ,133.33
+ ,133.57
+ ,134.13
+ ,133.92
+ ,132.62
+ ,132.3
+ ,133.26
+ ,132.6
+ ,134.38
+ ,134.17
+ ,135.46
+ ,135.09
+ ,134.96
+ ,133.85
+ ,132.59
+ ,131.15
+ ,130.91
+ ,131.07
+ ,130.78
+ ,129.95
+ ,131.41
+ ,131.21
+ ,130.68
+ ,130.46
+ ,131.12
+ ,132.99
+ ,133.02
+ ,133.39
+ ,134.07
+ ,135.6
+ ,135.66
+ ,135.53
+ ,135.82
+ ,136.9
+ ,137.97
+ ,138.09
+ ,136.91
+ ,134.76
+ ,135.13
+ ,134.66
+ ,132.95
+ ,132.25
+ ,134.3
+ ,134.3
+ ,134.76
+ ,134.81
+ ,134.51
+ ,135.11
+ ,134.32
+ ,133.51
+ ,134.02
+ ,132.76
+ ,133.39
+ ,132.05
+ ,131.87
+ ,133.03
+ ,132.57
+ ,132.1
+ ,130.7
+ ,129.2
+ ,129.77
+ ,131.02
+ ,131.55
+ ,133.17
+ ,133.08
+ ,133.24
+ ,130.74
+ ,129.91
+ ,130.03
+ ,131.13
+ ,129.55
+ ,130.22
+ ,130.61
+ ,129.27
+ ,129.68
+ ,130.1
+ ,130.83
+ ,130.95
+ ,131.73
+ ,131.86
+ ,132.44
+ ,132.35
+ ,133.16
+ ,133.62
+ ,132.54
+ ,132.69
+ ,133.5
+ ,133.36
+ ,134.23
+ ,132.41
+ ,133.02
+ ,132.88
+ ,130.76
+ ,130.33
+ ,129.79
+ ,128.65
+ ,129.14
+ ,127.35
+ ,127.74
+ ,126.31
+ ,125.95
+ ,126.36
+ ,126.15
+ ,125.6
+ ,126.2
+ ,126.73
+ ,125.68
+ ,122.49
+ ,122.07
+ ,123.4
+ ,123.01
+ ,123.03
+ ,122.33
+ ,122.42
+ ,122.68
+ ,124.69
+ ,123.3
+ ,124.17
+ ,124.38
+ ,123.19
+ ,122.16
+ ,120.66
+ ,120.92
+ ,120.67
+ ,120.68
+ ,121.1
+ ,120.86
+ ,121.48
+ ,123.48
+ ,121.72
+ ,123.16
+ ,123.84
+ ,124.57
+ ,124.3
+ ,124.22
+ ,124.43
+ ,123.33
+ ,122.86
+ ,121.25
+ ,122.16
+ ,122.62
+ ,123.44
+ ,124
+ ,124.75
+ ,124.8
+ ,125.93
+ ,126.28
+ ,126.04
+ ,125.04
+ ,123.76
+ ,125.34
+ ,126.99
+ ,126.34
+ ,127.42
+ ,126.18
+ ,125.3
+ ,123.5
+ ,125.32
+ ,124.65
+ ,124.03
+ ,125.11
+ ,125.46
+ ,124.7
+ ,124.48
+ ,124.76
+ ,125.81
+ ,124.95
+ ,123.66
+ ,122.66
+ ,119.34
+ ,117.84
+ ,120.97
+ ,117.38
+ ,118.06
+ ,116.99
+ ,115.55
+ ,114.17
+ ,115.32
+ ,112.49
+ ,111.93
+ ,112.08
+ ,111.63
+ ,109.53
+ ,111.35
+ ,110.79
+ ,113.06
+ ,112.62
+ ,110.65
+ ,112.36
+ ,113.74
+ ,111.73
+ ,109.86
+ ,109.32
+ ,109.99
+ ,109.84
+ ,111.13
+ ,112.43
+ ,111.77
+ ,112.15
+ ,112.89
+ ,112.12
+ ,113.1
+ ,111.09
+ ,110.76
+ ,109.59
+ ,109.99
+ ,110.25
+ ,108.31
+ ,108.79
+ ,108.14
+ ,109.88
+ ,109.93
+ ,110.46
+ ,109.56
+ ,111.49
+ ,111.85
+ ,111.35
+ ,110.95
+ ,112.49
+ ,113.11
+ ,112.54
+ ,112.84
+ ,111.5
+ ,111.52
+ ,111.57
+ ,112.48
+ ,112.31
+ ,113.79
+ ,114.01
+ ,113.64
+ ,112.62
+ ,113.27
+ ,113.51
+ ,112.92
+ ,113.66
+ ,113.14
+ ,113.48
+ ,113.23
+ ,110.56
+ ,109.5
+ ,109.78
+ ,109.49
+ ,109.66
+ ,109.93
+ ,109.82
+ ,108.54
+ ,108.23
+ ,106.19
+ ,106.49
+ ,107.15
+ ,107.74
+ ,107.54
+ ,107.07
+ ,107.54
+ ,107.81
+ ,108.38
+ ,108.42
+ ,106.86
+ ,106.41
+ ,106.46
+ ,106.84
+ ,107.69
+ ,107.04
+ ,111.04
+ ,111.93
+ ,111.98
+ ,112.07
+ ,112.05
+ ,113.14
+ ,112.49
+ ,113.2
+ ,113.52
+ ,113.22
+ ,113.85
+ ,113.68
+ ,114.26
+ ,114.1
+ ,114.8
+ ,114.98
+ ,115.1
+ ,114.21
+ ,114.24
+ ,113.35
+ ,114.23
+ ,114.43
+ ,114.28
+ ,113
+ ,113.16
+ ,112.59
+ ,113.65
+ ,113.18
+ ,113.21
+ ,113.11
+ ,112.78
+ ,112.57
+ ,111.87
+ ,111.94
+ ,113.18
+ ,113.67
+ ,115.15
+ ,114.41
+ ,112.88
+ ,112.44
+ ,113.48
+ ,112.78
+ ,112.59
+ ,113.31
+ ,113.21
+ ,112.5
+ ,113.72
+ ,114.09
+ ,113.97
+ ,112.5
+ ,111.28
+ ,111.35
+ ,110.92
+ ,110.73
+ ,109)
> par1 = '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- 5
> (n <- length(x))
[1] 491
> (np <- floor(n / par1))
[1] 98
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
       [,1]   [,2]   [,3]   [,4]   [,5]   [,6]   [,7]   [,8]   [,9]  [,10]
[1,] 126.64 124.40 120.11 113.65 114.98 116.70 117.59 118.62 123.23 122.53
[2,] 126.81 120.48 119.16 115.82 114.04 119.21 117.33 121.09 122.52 124.40
[3,] 125.84 118.54 116.90 117.59 115.02 118.39 116.20 122.40 123.64 125.45
[4,] 126.77 117.66 116.11 118.57 114.28 116.50 116.83 123.76 124.67 125.35
[5,] 124.34 116.97 114.98 118.07 115.04 115.46 118.99 125.33 124.71 124.30
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 127.03 129.87 129.91 134.08 132.57 126.82 125.08 131.17 130.90 131.06
[2,] 128.51 131.12 127.93 136.02 130.70 126.85 128.53 132.72 129.41 130.84
[3,] 128.10 132.68 131.17 132.80 130.50 128.28 130.34 133.36 128.67 131.41
[4,] 128.94 132.24 130.86 132.37 129.67 128.30 131.52 132.82 129.28 133.22
[5,] 129.67 133.63 133.48 133.05 127.80 126.82 132.59 132.90 130.91 132.06
      [,21]  [,22]  [,23]  [,24]  [,25]  [,26]  [,27]  [,28]  [,29]  [,30]
[1,] 132.48 136.33 138.03 133.28 133.77 136.53 131.02 131.57 132.49 133.86
[2,] 134.38 136.32 137.39 133.57 134.34 135.95 130.05 132.63 134.23 133.89
[3,] 135.22 137.48 137.55 134.84 134.50 134.32 128.21 132.06 134.92 135.33
[4,] 134.89 136.53 136.08 133.02 134.03 132.44 129.03 134.44 135.61 135.86
[5,] 136.09 136.80 134.78 133.49 135.51 133.61 130.34 134.10 134.53 136.22
      [,31]  [,32]  [,33]  [,34]  [,35]  [,36]  [,37]  [,38]  [,39]  [,40]
[1,] 137.38 135.77 132.55 134.32 131.63 134.13 132.60 134.96 131.07 130.68
[2,] 137.31 137.52 134.11 133.61 132.47 133.92 134.38 133.85 130.78 130.46
[3,] 136.89 135.61 134.19 134.75 132.45 132.62 134.17 132.59 129.95 131.12
[4,] 138.01 132.94 135.57 133.10 133.33 132.30 135.46 131.15 131.41 132.99
[5,] 136.72 134.12 135.05 133.26 133.57 133.26 135.09 130.91 131.21 133.02
      [,41]  [,42]  [,43]  [,44]  [,45]  [,46]  [,47]  [,48]  [,49]  [,50]
[1,] 133.39 135.82 134.76 134.30 135.11 133.39 132.10 131.55 129.91 130.61
[2,] 134.07 136.90 135.13 134.30 134.32 132.05 130.70 133.17 130.03 129.27
[3,] 135.60 137.97 134.66 134.76 133.51 131.87 129.20 133.08 131.13 129.68
[4,] 135.66 138.09 132.95 134.81 134.02 133.03 129.77 133.24 129.55 130.10
[5,] 135.53 136.91 132.25 134.51 132.76 132.57 131.02 130.74 130.22 130.83
      [,51]  [,52]  [,53]  [,54]  [,55]  [,56]  [,57]  [,58]  [,59]  [,60]
[1,] 130.95 133.16 133.36 130.76 127.35 126.15 122.49 122.33 124.17 120.92
[2,] 131.73 133.62 134.23 130.33 127.74 125.60 122.07 122.42 124.38 120.67
[3,] 131.86 132.54 132.41 129.79 126.31 126.20 123.40 122.68 123.19 120.68
[4,] 132.44 132.69 133.02 128.65 125.95 126.73 123.01 124.69 122.16 121.10
[5,] 132.35 133.50 132.88 129.14 126.36 125.68 123.03 123.30 120.66 120.86
      [,61]  [,62]  [,63]  [,64]  [,65]  [,66]  [,67]  [,68]  [,69]  [,70]
[1,] 121.48 124.57 122.86 124.00 126.04 126.34 125.32 124.70 123.66 117.38
[2,] 123.48 124.30 121.25 124.75 125.04 127.42 124.65 124.48 122.66 118.06
[3,] 121.72 124.22 122.16 124.80 123.76 126.18 124.03 124.76 119.34 116.99
[4,] 123.16 124.43 122.62 125.93 125.34 125.30 125.11 125.81 117.84 115.55
[5,] 123.84 123.33 123.44 126.28 126.99 123.50 125.46 124.95 120.97 114.17
      [,71]  [,72]  [,73]  [,74]  [,75]  [,76]  [,77]  [,78]  [,79]  [,80]
[1,] 115.32 109.53 110.65 109.32 111.77 111.09 108.31 110.46 110.95 111.50
[2,] 112.49 111.35 112.36 109.99 112.15 110.76 108.79 109.56 112.49 111.52
[3,] 111.93 110.79 113.74 109.84 112.89 109.59 108.14 111.49 113.11 111.57
[4,] 112.08 113.06 111.73 111.13 112.12 109.99 109.88 111.85 112.54 112.48
[5,] 111.63 112.62 109.86 112.43 113.10 110.25 109.93 111.35 112.84 112.31
      [,81]  [,82]  [,83]  [,84]  [,85]  [,86]  [,87]  [,88]  [,89]  [,90]
[1,] 113.79 113.51 113.23 109.66 106.19 107.07 106.86 107.04 112.05 113.22
[2,] 114.01 112.92 110.56 109.93 106.49 107.54 106.41 111.04 113.14 113.85
[3,] 113.64 113.66 109.50 109.82 107.15 107.81 106.46 111.93 112.49 113.68
[4,] 112.62 113.14 109.78 108.54 107.74 108.38 106.84 111.98 113.20 114.26
[5,] 113.27 113.48 109.49 108.23 107.54 108.42 107.69 112.07 113.52 114.10
      [,91]  [,92]  [,93]  [,94]  [,95]  [,96]  [,97]  [,98]
[1,] 114.80 113.35 113.16 113.11 113.18 112.44 113.21 112.50
[2,] 114.98 114.23 112.59 112.78 113.67 113.48 112.50 111.28
[3,] 115.10 114.43 113.65 112.57 115.15 112.78 113.72 111.35
[4,] 114.21 114.28 113.18 111.87 114.41 112.59 114.09 110.92
[5,] 114.24 113.00 113.21 111.94 112.88 113.31 113.97 110.73
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
 [1] 126.080 119.610 117.452 116.740 114.672 117.252 117.388 122.240 123.754
[10] 124.406 128.450 131.908 130.670 133.664 130.248 127.414 129.612 132.594
[19] 129.834 131.718 134.612 136.692 136.766 133.640 134.430 134.570 129.730
[28] 132.960 134.356 135.032 137.262 135.192 134.294 133.808 132.690 133.246
[37] 134.340 132.692 130.884 131.654 134.850 137.138 133.950 134.536 133.944
[46] 132.582 130.558 132.356 130.168 130.098 131.866 133.102 133.180 129.734
[55] 126.742 126.072 122.800 123.084 122.912 120.846 122.736 124.170 122.466
[64] 125.152 125.434 125.748 124.914 124.940 120.894 116.430 112.690 111.470
[73] 111.668 110.542 112.406 110.336 109.010 110.942 112.386 111.876 113.466
[82] 113.342 110.512 109.236 107.022 107.844 106.852 110.812 112.880 113.822
[91] 114.666 113.858 113.158 112.454 113.858 112.920 113.498 111.356
> arr.sd
 [1] 1.0497381 2.9840409 2.1329955 2.0146216 0.4755208 1.5174222 1.0408266
 [8] 2.5647125 0.9438379 1.1738526 0.9837429 1.4530898 2.0166433 1.4595993
[15] 1.7310604 0.7998000 2.9474005 0.8329346 1.0168235 0.9580814 1.3444962
[22] 0.4817364 1.3244357 0.7038111 0.6661456 1.6783176 1.1111931 1.2590671
[29] 1.1639072 1.1026650 0.5019661 1.7427765 1.1495564 0.7053864 0.7767883
[36] 0.7941536 1.1039701 1.7355460 0.5702456 1.2560175 1.0513087 0.9279386
[43] 1.2691139 0.2435775 0.8799034 0.6410304 1.1265523 1.1433853 0.5906945
[50] 0.6438711 0.5960956 0.4784558 0.6788593 0.8571639 0.7624762 0.4560373
[57] 0.5210566 0.9744896 1.5371955 0.1793878 1.0679326 0.4880061 0.8215717
[64] 0.9341146 1.1994499 1.4651689 0.5814895 0.5144414 2.3726104 1.5616498
[71] 1.5025146 1.4222342 1.5067415 1.2450984 0.5629654 0.5983143 0.8512638
[78] 0.9264826 0.8406723 0.4782573 0.5443620 0.3030182 1.5806866 0.7903986
[85] 0.6662357 0.5726517 0.5127085 2.1492254 0.5959446 0.4038812 0.4166293
[92] 0.6398984 0.3767891 0.5374291 0.9254026 0.4540374 0.6522040 0.6885710
> arr.range
 [1] 2.47 7.43 5.13 4.92 1.00 3.75 2.79 6.71 2.19 2.92 2.64 3.76 5.55 3.65 4.77
[16] 1.48 7.51 2.19 2.24 2.38 3.61 1.16 3.25 1.82 1.74 4.09 2.81 2.87 3.12 2.36
[31] 1.29 4.58 3.02 1.65 1.94 1.83 2.86 4.05 1.46 2.56 2.27 2.27 2.88 0.51 2.35
[46] 1.52 2.90 2.50 1.58 1.56 1.49 1.08 1.82 2.11 1.79 1.13 1.33 2.36 3.72 0.43
[61] 2.36 1.24 2.19 2.28 3.23 3.92 1.43 1.33 5.82 3.89 3.69 3.53 3.88 3.11 1.33
[76] 1.50 1.79 2.29 2.16 0.98 1.39 0.74 3.74 1.70 1.55 1.35 1.28 5.03 1.47 1.04
[91] 0.89 1.43 1.06 1.24 2.27 1.04 1.59 1.77
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
   0.395034     0.005095  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       -4.989          1.012  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    0.66519      0.01503  

> postscript(file="/var/www/html/rcomp/tmp/1a8qc1292755606.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2a8qc1292755606.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3er6i1292755606.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4z9n61292755606.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5dj2w1292755606.tab") 
> 
> try(system("convert tmp/1a8qc1292755606.ps tmp/1a8qc1292755606.png",intern=TRUE))
character(0)
> try(system("convert tmp/2a8qc1292755606.ps tmp/2a8qc1292755606.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.704   0.374   8.855