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51 59 60 47 55 57 57 50 58 64 48 58 39 54 58 57 59 63 55 59 61 62 50 55 59 60 62 62 48 53 55 57 62 60 64 66 67 65 72 59 59 58 64 62 63 64 63 65 66 62 66 66 68 63 60 59 50 58 70 66 66 64 69 59 60 66 62 66 68 63 67 63 66 64 65 70 66 69 68 60 72 69 74 70 73 70 57 63 64 61 59 68 63 63 68 59 67 73 66 69 65 68 71 73 72 77 62 67 65 60 61 69 66 67 68 68 65 69 71 64 68 70 65 70 66 73 72 75 73 69 75 66 58 69 68 66 73 73 68 70 71 72 72 75 70 70 69 67 67 73 76 73 76 79 73 78 78 66 68 66 65 69 73 70 71 73 73 72 72 72 73 74 73 75 71 74 75 75 78 75 78 75 75 77 73 75 69 68 72 76 78 71 78 75 79 81 78 79 69 69 74 77 76 78 72 74 80 75 80 68 76 76 77 81 77 84 84
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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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