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62 71 54 65 52 84 42 66 65 78 66 61 71 69 72 68 70 68 67 77 72 69 71 62 64 58 52 59 68 76 65 59 69 63 75 63 60 73 63 70 66 63 64 61 62 61 66 56 66 53 59 71 71 64 66 62 65 68 60 65 68 64 74 69 68 72 67 66 51 56 67 69 56 55 67 76 64 68 64 65 71 63 60 72 70 61 61 62 71 51 56 70 73 76 52 57 60 60 62 59 61 69 59 66 67 75 69 58 60 74 55 63 68 62 72 62 75 58 47 19 50 79 71 48 66 74 66 71 53 60 70 69 59 72 71 74 80 73 67 61 74 32 69 64 60 59 78 60 68 73 67 65 74 55 49 53 64 57 67 70 75 65 65 69 48 68 74 67 65 74 69 63 68 70 78 74 62 69 65 67 52 53 76 63 41 72 52 65 63 56 56 64 75 65 61 71 72 62 66 63 71 64 78 60 68 68 60 65 64 69 74 76 73 76 55 62 78 67 75 59 70 59 63 67 58 71 53 64 67 72 57 62 74 54 66 64 74 71 63 70 66 78 72 72 58 84 67 63 55 58 69 54 58 67 77 80 67 71 79 76 72 81 52 76 60 77 64 67 79 40 71 73 70 66 74 58 51 75 50 77 71
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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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