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54 59 49 65 68 71 48 50 46 40 37 47 32 42 31 60 36 54 46 42 21 20 7 45 51 47 33 8 46 28 34 33 46 56 58 51 32 24 29 45 54 41 41 39 38 57 51 51 61 40 39 37 43 29 34 46 43 51 30 45 63 69 58 54 55 41 32 61 61 52 46 58 67 69 43 25 31 39 53 43 48 58 59 14 12 33 39 52 28 13 18 34 44 54 37 40 45 41 55 39 38 52 31 38 40 38 44 63 54 39 50 41 37 30 44 51 14 -7 10 34 58 36 31 42 31 23 27 51 46 41 51 46 59 74 67 71 53 58 51 32 59 55 55 33 54 71 36 48 35 44 51 63 60 41 21 44 48 48 28 36 45 39 47 36 49 55 33 34 52 11 42 29 37 49 60 23 13 12 19 17 35 34 43 57 42 49 41 55 34 17 36 54 50 60 73 64 71 39 73 62 58 72 31 41 45 35 27 36 57 57 62 62 43 60 76 75 48 54 67 48 60 71 62 36 54 57 58 63 29 32 48 31 33 34 49 36 46 34 40 48 46 28 34 35 28 35 33 25 26 43 50 33 38 35 39 39 46 40 9 5 27 35 19 38 30 32 30 43 26 43 32 47 50 67 42 33 30 28 39 42 42 47 46 45 49 43 40 29 41 46 54 54 36 69 64 57 48 43 74 66
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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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