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Type 'q()' to quit R. > x <- c(5115,5105,5094,5074,5280,5270,5115,5012,5022,5022,5032,5053,5053,4960,4919,4960,5105,5084,4888,4722,4691,4629,4671,4722,4702,4660,4578,4660,4733,4712,4474,4371,4268,4185,4175,4237,4154,4123,4092,4268,4288,4185,3906,3782,3586,3503,3544,3606,3606,3555,3544,3710,3844,3782,3575,3472,3255,3121,3224,3327,3327,3193,3183,3358,3472,3431,3224,3090,2800,2687,2728,2904,2914,2656,2749,2976,3079,3017,2738,2542,2315,2139,2211,2366,2325,2098,2170,2397,2521,2449,2170,2046,1860,1664,1695,1850,1870,1684,1715,1974,2036,1932,1550,1354,1095,837,920,1033,1013,816,930,1209,1333,1271,1023,827,620,382,424,496) > 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] 120 > (np <- floor(n / par1)) [1] 30 > 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] [,11] [,12] [,13] [,14] [1,] 5115 5280 5022 5053 5105 4691 4702 4733 4268 4154 4288 3586 3606 3844 [2,] 5105 5270 5022 4960 5084 4629 4660 4712 4185 4123 4185 3503 3555 3782 [3,] 5094 5115 5032 4919 4888 4671 4578 4474 4175 4092 3906 3544 3544 3575 [4,] 5074 5012 5053 4960 4722 4722 4660 4371 4237 4268 3782 3606 3710 3472 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [1,] 3255 3327 3472 2800 2914 3079 2315 2325 2521 1860 1870 2036 [2,] 3121 3193 3431 2687 2656 3017 2139 2098 2449 1664 1684 1932 [3,] 3224 3183 3224 2728 2749 2738 2211 2170 2170 1695 1715 1550 [4,] 3327 3358 3090 2904 2976 2542 2366 2397 2046 1850 1974 1354 [,27] [,28] [,29] [,30] [1,] 1095 1013 1333 620 [2,] 837 816 1271 382 [3,] 920 930 1023 424 [4,] 1033 1209 827 496 > 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] 5097.00 5169.25 5032.25 4973.00 4949.75 4678.25 4650.00 4572.50 4216.25 [10] 4159.25 4040.25 3559.75 3603.75 3668.25 3231.75 3265.25 3304.25 2779.75 [19] 2823.75 2844.00 2257.75 2247.50 2296.50 1767.25 1810.75 1718.00 971.25 [28] 992.00 1113.50 480.50 > arr.sd [1] 17.56891 129.21139 14.61449 56.72742 180.56278 38.96473 51.92302 [8] 178.44233 43.91943 76.79138 235.97228 45.81394 75.80842 174.19984 [15] 85.51559 90.18638 179.39598 95.09425 147.25573 250.06266 102.11554 [22] 137.49303 225.39521 102.19385 135.88567 320.22908 115.14737 165.68042 [29] 233.28023 104.23531 > arr.range [1] 41 268 31 134 383 93 124 362 93 176 506 103 166 372 206 175 382 217 320 [20] 537 227 299 475 196 290 682 258 393 506 238 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 198.26705 -0.02221 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 8.6689 -0.5092 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 434.21770 -0.04958 > postscript(file="/var/wessaorg/rcomp/tmp/1xvyr1311848874.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/wessaorg/rcomp/tmp/29t361311848874.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3ebvh1311848874.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/wessaorg/rcomp/tmp/4yjpv1311848874.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/wessaorg/rcomp/tmp/5b54y1311848874.tab") > > try(system("convert tmp/1xvyr1311848874.ps tmp/1xvyr1311848874.png",intern=TRUE)) character(0) > try(system("convert tmp/29t361311848874.ps tmp/29t361311848874.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.666 0.131 0.808