R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- c(131676
+ ,135050
+ ,129070
+ ,137792
+ ,139762
+ ,142917
+ ,144198
+ ,142648
+ ,152170
+ ,136022
+ ,138142
+ ,138135
+ ,135027
+ ,132911
+ ,133976
+ ,137012
+ ,119610
+ ,118106
+ ,120383
+ ,133185
+ ,131416
+ ,134248
+ ,134397
+ ,127728
+ ,131837
+ ,125955
+ ,134187
+ ,143291
+ ,145074
+ ,149812
+ ,144668
+ ,147253
+ ,145568
+ ,155564
+ ,155872
+ ,156323
+ ,158010
+ ,155598
+ ,154785
+ ,157294
+ ,162938
+ ,157283
+ ,166074
+ ,169282
+ ,172552
+ ,174055
+ ,175409
+ ,173696
+ ,171283
+ ,173322
+ ,170717
+ ,174229
+ ,175339
+ ,173511
+ ,175839
+ ,173816
+ ,173990
+ ,174777
+ ,174819
+ ,176726
+ ,176199
+ ,180952
+ ,176663
+ ,182346
+ ,180605
+ ,182497
+ ,187856
+ ,190020
+ ,190108
+ ,193288
+ ,193230
+ ,199068
+ ,195076
+ ,191563
+ ,191067
+ ,186665
+ ,185508
+ ,184371
+ ,183046
+ ,175714
+ ,175768
+ ,171029
+ ,170465
+ ,170102
+ ,156389
+ ,124291
+ ,99360
+ ,86675
+ ,85056
+ ,128236
+ ,164257
+ ,162401
+ ,152779
+ ,156005
+ ,153387
+ ,153190
+ ,148840
+ ,144211
+ ,145953
+ ,145542
+ ,150271
+ ,147489
+ ,143824
+ ,134754
+ ,131736
+ ,126304
+ ,125511
+ ,125495
+ ,130133
+ ,126257
+ ,110323
+ ,98417
+ ,105749
+ ,120665
+ ,124075
+ ,127245
+ ,146731
+ ,144979
+ ,148210
+ ,144670
+ ,142970
+ ,142524
+ ,146142
+ ,146522
+ ,148128
+ ,148798
+ ,150181
+ ,152388
+ ,155694
+ ,160662
+ ,155520
+ ,158262
+ ,154338
+ ,158196
+ ,160371
+ ,154856
+ ,150636
+ ,145899
+ ,141242
+ ,140834
+ ,141119
+ ,139104
+ ,134437
+ ,129425
+ ,123155
+ ,119273
+ ,120472
+ ,121523
+ ,121983
+ ,123658
+ ,124794
+ ,124827
+ ,120382
+ ,117395
+ ,115790
+ ,114283
+ ,117271
+ ,117448
+ ,118764
+ ,120550
+ ,123554
+ ,125412
+ ,124182
+ ,119828
+ ,115361
+ ,114226
+ ,115214
+ ,115864
+ ,114276
+ ,113469
+ ,114883
+ ,114172
+ ,111225
+ ,112149
+ ,115618
+ ,118002
+ ,121382
+ ,120663)
> 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 <- as.numeric(par1)
> (n <- length(x))
[1] 178
> (np <- floor(n / par1))
[1] 44
> 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,] 131676 139762 152170 135027 119610 131416 131837 145074 145568 158010
[2,] 135050 142917 136022 132911 118106 134248 125955 149812 155564 155598
[3,] 129070 144198 138142 133976 120383 134397 134187 144668 155872 154785
[4,] 137792 142648 138135 137012 133185 127728 143291 147253 156323 157294
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 162938 172552 171283 175339 173990 176199 180605 190108 195076 185508
[2,] 157283 174055 173322 173511 174777 180952 182497 193288 191563 184371
[3,] 166074 175409 170717 175839 174819 176663 187856 193230 191067 183046
[4,] 169282 173696 174229 173816 176726 182346 190020 199068 186665 175714
      [,21]  [,22]  [,23]  [,24]  [,25]  [,26]  [,27]  [,28]  [,29]  [,30]
[1,] 175768 156389  85056 152779 148840 150271 131736 130133 105749 146731
[2,] 171029 124291 128236 156005 144211 147489 126304 126257 120665 144979
[3,] 170465  99360 164257 153387 145953 143824 125511 110323 124075 148210
[4,] 170102  86675 162401 153190 145542 134754 125495  98417 127245 144670
      [,31]  [,32]  [,33]  [,34]  [,35]  [,36]  [,37]  [,38]  [,39]  [,40]
[1,] 142970 148128 155694 154338 150636 141119 123155 121983 120382 117271
[2,] 142524 148798 160662 158196 145899 139104 119273 123658 117395 117448
[3,] 146142 150181 155520 160371 141242 134437 120472 124794 115790 118764
[4,] 146522 152388 158262 154856 140834 129425 121523 124827 114283 120550
      [,41]  [,42]  [,43]  [,44]
[1,] 123554 115361 114276 111225
[2,] 125412 114226 113469 112149
[3,] 124182 115214 114883 115618
[4,] 119828 115864 114172 118002
> 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] 133397.0 142381.2 141117.2 134731.5 122821.0 131947.2 133817.5 146701.8
 [9] 153331.8 156421.8 163894.2 173928.0 172387.8 174626.2 175078.0 179040.0
[17] 185244.5 193923.5 191092.8 182159.8 171841.0 116678.8 134987.5 153840.2
[25] 146136.5 144084.5 127261.5 116282.5 119433.5 146147.5 144539.5 149873.8
[33] 157534.5 156940.2 144652.8 136021.2 121105.8 123815.5 116962.5 118508.2
[41] 123244.0 115166.2 114200.0 114248.5
> arr.sd
 [1]  3818.0800  1872.5415  7435.7421  1748.6186  6973.7146  3129.3781
 [7]  7202.4306  2363.8416  5185.2098  1487.8253  5112.1490  1177.0995
[13]  1660.8133  1137.1108  1162.9460  3071.7416  4423.3867  3737.5894
[19]  3449.3018  4413.3712  2645.6360 30740.9305 37179.4794  1465.2252
[25]  1949.6636  6757.4525  3006.8105 14674.4532  9510.4361  1647.5008
[31]  2083.5773  1881.5540  2432.8422  2855.5651  4603.2049  5212.5095
[37]  1646.6263  1337.0935  2609.8859  1515.3733  2404.5252   685.8408
[43]   579.4854  3136.5451
> arr.range
 [1]  8722  4436 16148  4101 15079  6669 17336  5144 10755  3225 11999  2857
[13]  3512  2328  2736  6147  9415  8960  8411  9794  5666 69714 79201  3226
[25]  4629 15517  6241 31716 21496  3540  3998  4260  5142  6033  9802 11694
[37]  3882  2844  6099  3279  5584  1638  1414  6777
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 14839.1888      -0.0687  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      16.3781        -0.7037  

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

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

Coefficients:
(Intercept)     arr.mean  
 32816.9836      -0.1520  

> postscript(file="/var/www/rcomp/tmp/1l3dg1305058463.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/rcomp/tmp/2unbn1305058463.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/3sq1x1305058463.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4vdtk1305058463.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/rcomp/tmp/5t0ra1305058463.tab") 
> 
> try(system("convert tmp/1l3dg1305058463.ps tmp/1l3dg1305058463.png",intern=TRUE))
character(0)
> try(system("convert tmp/2unbn1305058463.ps tmp/2unbn1305058463.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.380   0.312   1.683