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Data:
0.0976999042077651 0.0888998338005906 0.0964998334679063 0.0894998341831167 0.0853998438657789 0.0842998482610295 0.0836998497391663 0.0861998477733592 0.0906998413388313 0.0956998327961495 0.095599828849401 0.0969998524271482 -0.357053321260274 -1.64125592174998 -5.65398562941077 -3.57369093017378 3.08909186160842 -1.14294096349874 0.602499286559887 0.166822064597347 -2.02531351834469 -1.51546107389643 0.0724805852747878 -2.12205929540466 2.19628766173121 -0.0605079650571812 3.64463341109045 4.3312299372585 2.20072805798757 2.74253723998927 2.80660340500022 2.42310540764882 -1.664502969128 1.80722045286534 -0.0879161686365307 -0.790544927696883 3.70734995450548 2.45145951417313 0.471526918886696 3.41122052361345 0.187591405261646 1.87810105953099 4.50494118727212 1.9031677843587 1.52467514737968 1.72575668554543 -3.58861424781686 6.96148170420439 1.69928770794081 3.04405183004109 2.48606121085736 -0.807396900146041 1.53657589478381 -1.38161897704946 2.77598793097358 -5.93296184347235 -0.263889052860067 -3.02535674547065 4.0012575934818 4.32801939555623 -2.04085540667922 6.68357991579588 -2.06004642382633 3.522754668406 -3.36850476440946 -0.711479229976281 -1.61039660855169 -1.94921198196442 -1.21319020567838 -2.44756150052018 -1.41356427888564 5.47243063881544 1.89600852094512 3.88035094112904 0.922325836564759 -3.08706584611076 1.06860614455855 0.881413679492219 -1.57557832654175 0.527939913027753 -3.86831652628551 1.40765149496435 -1.40354501070749 -1.55576677799834 0.914900847927305 2.99711419297897 1.32395378714095 2.39203609300244 -0.726259896583282 2.29567767446795 -2.53527156152751 3.74269940625232 -1.86879168954026 4.51712030941218 4.45668746161051 1.59689203792215 3.26315868802412 -0.543077103435425 -3.46548932688626 0.0598501475597718 -3.52257936759703 0.879330630495331 0.808267955488759 -0.891900331296483 0.443994317595385 0.141298011897711 -2.80826062918138 5.52761466380316 2.17891836739269 0.581613942878553 2.24179847901961 -2.07361858024247 4.49698865661718 -0.910119263072599 4.55376468685512 7.48120523981561 6.07660728911893 2.1751579748916 2.53634277143853 7.0905286026385 6.64550874513171 6.85412406071121 6.41334363341769 1.451396131662 5.88118896677921 0.396276524675632 4.5197815049283 1.41617888835173 -0.134041291023127 0.807840315036697 5.04424629212873 -1.3362225226509 2.23050898982359 -2.4124794822725 0.280947418259945 -0.629883736968921 2.82350012327787 -0.539447361745164 -0.478633901306396 1.98286680956942 0.566751504683537 -2.95578003485252 -2.8565769057602 -0.84387697300368 0.657716626503226 14.2882970976304 -15.9996183800875 8.39265012689809 -5.40811611431774 -0.387605883172688 -1.8948835378665 -6.1997974605813 -3.79506066565307 -9.84732540147536 -1.85489547796836 -5.02361465754457 -2.03333959245047 -3.16576613387049 6.72791511770907 -9.82848701501875 -1.71062398205383 1.46570354878151 2.64418036004429 -3.28738353946084 -1.41781549259528 4.74181775442066 4.68722306762713 5.46484582359931 -4.51374511743435 2.18551106502422 -6.82074461724613 -4.71034867081783 -2.21582759263371 -6.47891425453943 -4.22546886960864 -9.6047723905143 -8.68320806099863 -9.1732300352678 -10.3017333729288 -7.38105099800202 -0.796877816411444 -5.86095189446579 -5.79007969724407 -5.75147519627957 -8.68514523795461 -5.87071349201609 -9.60690856291488 -9.53894275797437 -2.52198658144077 -3.74119764281139 2.19669722197803 -5.76158272034317 11.5282655390469 1.77267041237508 12.6725222840074 3.46546572748846 -1.0804696213614 -0.306116395111087 3.86481926030857 7.42235826762557 -2.95271702955756 3.61466876312377 3.26319794373134 4.58485703523785 4.04330871807009 -0.212109037663633 -0.101392533947272 -6.66116675533387 2.74832705448637 5.34508004769503 4.3318058751711 2.7946809664538
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R Code
library(MASS) library(car) 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') print(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$estimate[2])^2),min(x),max(x),add=T) dev.off() bitmap(file='test3.png') qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$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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Computing time
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R Server
Big Analytics Cloud Computing Center
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