R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1686,1591,2304,1712,1471,1377,1966,2453,1984,2596,4087,5179,1530,1523,1633,1976,1170,1480,1781,2472,1981,2273,3857,4551,1510,1329,1518,1790,1537,1449,1954,1897,1706,2514,3593,4524,1609,1638,2030,1375,1320,1245,1600,2298,2191,2511,3440,4923,1609,1435,2061,1789,1567,1404,1597,3159,1759,2504,4273,5274,1771,1682,1846,1589,1896,1379,1645,2512,1771,3727,4388,5434,1606,1523,1577,1605,1765,1403,2584,3318,1562,2349,3987,5891,1389,1442,1548,1935,1518,1250,1847,1930,2638,3114,4405,7242,1853,1779,2108,2336,1728,1661,2230,1645,2421,3740,4988,6757,1757,1394,1982,1650,1654,1406,1971,1968,2608,3845,4514,6694,1720,1321,1859,1628,1615,1457,1899,1605,2424,3116,4286,6047,1902,2049,1874,1279,1432,1540,2214,1857,2408,3252,3627,6153,1577,1667,1993,1997,1783,1625,2076,1773,2377,3088,4096,6119,1494,1564,1898,2121,1831,1515,2048,2795,1749,3339,4227,6410,1197,1968,1720,1725,1674,1693,2031,1495,2968,3385,3729,5999,1070,1402,1897,1862,1670,1688,2031)
> par1 = '4'
> par1 <- as.numeric(par1)
> par1 <- 24
> (n <- length(x))
[1] 187
> (np <- floor(n / par1))
[1] 7
> 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]
 [1,] 1686 1510 1609 1606 1853 1720 1577
 [2,] 1591 1329 1435 1523 1779 1321 1667
 [3,] 2304 1518 2061 1577 2108 1859 1993
 [4,] 1712 1790 1789 1605 2336 1628 1997
 [5,] 1471 1537 1567 1765 1728 1615 1783
 [6,] 1377 1449 1404 1403 1661 1457 1625
 [7,] 1966 1954 1597 2584 2230 1899 2076
 [8,] 2453 1897 3159 3318 1645 1605 1773
 [9,] 1984 1706 1759 1562 2421 2424 2377
[10,] 2596 2514 2504 2349 3740 3116 3088
[11,] 4087 3593 4273 3987 4988 4286 4096
[12,] 5179 4524 5274 5891 6757 6047 6119
[13,] 1530 1609 1771 1389 1757 1902 1494
[14,] 1523 1638 1682 1442 1394 2049 1564
[15,] 1633 2030 1846 1548 1982 1874 1898
[16,] 1976 1375 1589 1935 1650 1279 2121
[17,] 1170 1320 1896 1518 1654 1432 1831
[18,] 1480 1245 1379 1250 1406 1540 1515
[19,] 1781 1600 1645 1847 1971 2214 2048
[20,] 2472 2298 2512 1930 1968 1857 2795
[21,] 1981 2191 1771 2638 2608 2408 1749
[22,] 2273 2511 3727 3114 3845 3252 3339
[23,] 3857 3440 4388 4405 4514 3627 4227
[24,] 4551 4923 5434 7242 6694 6153 6410
> arr.mean <- array(NA,dim=np*2)
> arr.sd <- array(NA,dim=np*2)
> arr.range <- array(NA,dim=np*2)
> 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] 2276.375 2145.875 2419.625 2476.167 2695.375 2440.167 2548.417       NA
 [9]       NA       NA       NA       NA       NA       NA
> arr.sd
 [1] 1066.162 1002.549 1254.576 1529.344 1572.464 1358.756 1377.375       NA
 [9]       NA       NA       NA       NA       NA       NA
> arr.range
 [1] 3669 3602 3916 5637 5286 4776 4813   NA   NA   NA   NA   NA   NA   NA
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -1406.372        1.118  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -9.571          2.148  

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

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

Coefficients:
(Intercept)     arr.mean  
  -4241.556        3.611  

> postscript(file="/var/www/html/rcomp/tmp/14d5f1198503456.ps",horizontal=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/268p31198503457.ps",horizontal=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 
> 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/3gbgn1198503457.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4tsso1198503457.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5vcqa1198503457.tab") 
> 
> system("convert tmp/14d5f1198503456.ps tmp/14d5f1198503456.png")
> system("convert tmp/268p31198503457.ps tmp/268p31198503457.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.741   0.279   0.881