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Data:
-2.44495 -1.16038 -0.60693 -7.05026 -6.48043 -2.53846 0.480307 -1.81602 -3.5781 -6.5739 -2.59754 -8.38308 -1.30838 -3.39781 -4.2749 -0.533569 -2.94169 -3.29023 -3.91867 -2.64762 -5.92087 1.27741 -3.66243 -1.36758 -2.32758 -5.42781 0.813972 0.577655 -4.53862 -1.55758 -4.27982 -1.98905 -3.58331 -4.23511 -1.79133 -2.0139 -2.78755 0.497376 -5.15182 -1.89245 -6.99434 -2.14226 -1.17065 -2.73472 0.62781 -2.96209 -2.00383 -4.59142 -0.141758 1.16158 -0.756651 -4.43327 -2.17543 -0.523044 -0.126924 -2.37404 -6.32748 1.03744 -2.2701 0.365162 -6.06374 0.237082 -4.59059 0.358888 -4.83602 -2.41242 -3.78637 -4.57844 1.16707 -0.269101 -2.58362 -1.15655 -3.89457 0.550525 -0.546752 -1.43065 0.25285 -1.42454 -1.58633 -5.42368 -1.81187 1.36136 -1.66961 -7.35486 -3.18914 -2.23094 -0.765955 0.622673 -3.23026 0.660384 0.635742 -6.5155 -4.2161 -2.87222 -4.19501 -2.84805 -5.4417 0.0594222 1.99465 -4.4413 -1.12946 -1.64422 -3.28457 -3.31468 1.66916 -4.03799 1.15479 -6.93766 -4.64612 -3.38979 -0.571597 -0.406872 -6.74431 0.286642 4.93156 4.6665 0.053712 1.50608 1.1955 3.84174 -2.55022 2.71681 3.53361 4.49698 -1.96913 0.523129 3.12017 0.00236798 4.63572 2.27575 2.46437 0.696264 2.41944 1.72816 0.704122 -0.13633 4.75351 -2.05799 3.75277 0.938164 -0.0993215 5.67783 0.986981 4.90236 2.50432 2.26947 0.184141 1.12572 1.0956 4.45421 -3.04871 1.28708 4.55291 2.77879 2.96905 0.228428 3.01566 2.97218 -0.0879362 -0.205283 3.8451 3.46573 2.01648 5.45284 3.87444 0.288623 4.48667 4.10826 2.04702 -1.81245 3.18827 4.5255 0.81333 1.98147 2.06674 4.4046 -0.701673 5.38317 1.36839 -3.11701 -1.36277 0.711947 4.68116 2.03938 -0.0429516 2.37285 5.41973 0.558481 1.14327 0.904081 -1.18012 2.15605 -2.17335 5.40277 1.24869 1.67037 0.773512 1.32753 3.38028 3.12494 2.13066 1.36483 0.611084 3.01358 1.54191 3.53495 -1.74096 0.825083 4.53069 3.45209 -0.420339 2.67689 -1.57792 2.06041 1.82527 -0.521428 2.8814 4.83123 -0.635476 2.24849 5.25721 -3.30466 0.61118 4.1699 5.28519 3.91833 4.80242 3.84884 3.7055 5.62694 5.74466 3.44894 1.83213 0.249697 -2.11049 -6.58651 1.57779 0.337516 -2.03739 0.666342 0.0836842 0.0480069 2.58015 4.31689 -0.453489 1.69858 2.0102 1.71785 2.06868 1.12502 0.165255 -0.994904 1.70827 1.56879 -0.224132 3.08975 -3.11908 -3.54644 -0.540604 -5.2376 -0.444241 0.42942 -2.68138 2.56004 3.88497 0.996637 1.85048 3.88073 4.04711 -0.457924 3.8767 1.27432 2.01152 4.00201 1.86748 1.77321 3.47481 -2.31342
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R Code
library(MASS) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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