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840.875 1051.8 854.835 849.2 625.1 964.775 887.225 1010.45 1131.25 718.2 1088.5 1271.375 1098.375 1098.375 1195.05 1361.375 1361.375 1100.625 1190.375 1250.485 1087.575 992.05 810 1064.95 937.25 1039 1122.956 1079.5 1079.5 889.5 784.5 793.75 924.5 762.43 811.5 942.94 812.615 911.735 1009.25 1116.01 1116.01 988.16 1067.52 1082.53 1043.215 871.83 904.485 689.56 1082.78 1098.85 713.5 704.5 0 652.25 563 586 538.75 353.6 321.275 388.4 329.6 323 520.25 607.725 803.45 677.25 711 962.5 935.6 722.255 594.25 853.75 766.5 758.05 756.85 685.4 696.525 610.025 708.325 619.1 740.525 730.5 489.75 766.525 690.882 804.975 529.25 743.75 771.15 830.5 600 856.1 702.75 533.775 311.25 590 738 797.05 531.3 820 533.25 633.25 634.275 747.3 220.375 195.75 123.25 161.75 126.75 285.1 461.5 463.625 325.875 177 223 168.45 251.75 131.5 110.375 164.125
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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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