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36 44 58 44 38 52 43 26 43 47 41 50 14 37 60 64 55 59 44 29 66 55 43 60 48 53 58 47 51 58 53 59 51 52 49 56 42 60 53 55 51 39 66 56 46 37 51 53 49 25 63 64 46 59 54 51 56 51 56 60 51 64 43 60 56 58 52 64 63 58 51 60 49 54 41 56 59 55 51 22 49 62 59 51 50 31 34 45 51 51 50 60 47 53 34 40 59 52 40 69 52 49 58 54 58 50 48 62 55 52 47 52 64 68 58 46 32 63 57 45 61 30 41 44 50 53 63 64 55 44 53 42 47 46 56 64 57 66 55 55 62 46 56 68 29 51 51 39 45 69 66 45 59 60 41 53 46 66 53 58 51 58 58 54 67 56 64 56 56 62 45 54 47 65 59 65 41 56 58 35 62 54 41 52 52 58 58 54 53 53 37 55 55 53 68 74 63 61 57 71 63 61 67 64 48 60 76 66 66 53 69 47 55 66 60 50 77
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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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