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57.42 56.12 59.15 63.77 63.96 57.81 55.3 51.8 53.26 53.38 45.85 44.23 40.22 44.61 49.14 42.94 41.84 37.75 35.54 37.13 33.19 32.67 30.52 30.7 29.59 28.76 29.08 26.95 29.58 28.24 27.28 25.48 24.87 29.87 32.33 30.23 27.46 24.46 27.34 28.37 26.09 25.59 24.67 25.61 25.97 24.31 20.36 19.82 19.32 19.2 21.74 26.29 25.9 25.36 27.64 28.57 25.38 25.71 27.6 25.85 26.54
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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