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50 62 54 71 54 65 73 52 84 42 66 65 78 73 75 72 66 70 61 81 71 69 71 72 68 70 68 61 67 76 70 60 72 69 71 62 70 64 58 76 52 59 68 76 65 67 59 69 76 63 75 63 60 73 63 70 75 66 63 63 64 70 75 61 60 62 73 61 66 64 59 64 60 56 78 53 67 59 66 68 71 66 73 72 71 59 64 66 78 68 73 62 65 68 65 60 71 65 68 64 74 69 76 68 72 67 63 59 73 66 62 69 66 51 56 67 69 57 56 55 63 67 65 47 76 64 68 64 65 71 63 60 68 72 70 61 61 62 71 71 51 56 70 73 76 68 48 52 60 59 57 79 60 60 59 62 59 61 71 57 66 63 69 58 59 48 66 73 67 61 68 75 62 69 58 60 74 55 62 63 69 58 58 68 72 62 62 65 69 66 72 62 75 58 66 55 47 72 62 64 64 19 50 68 70 79 69 71 48 73 74 66 71 74 78 75 53 60 70 69 65 78 78 59 72 70 63 63 71 74 67 66 62 80 73 67 61 73 74 32 69 69 84 64 58 59 78 57 60 68 68 73 69 67 60 65 66 74 81 72 55 49 74 53 64 65 57 51 80 67 70 74 75 70 69 65 55 71 65
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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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