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Data:
110.40 96.40 101.90 106.20 81.00 94.70 101.00 109.40 102.30 90.70 96.20 96.10 106.00 103.10 102.00 104.70 86.00 92.10 106.90 112.60 101.70 92.00 97.40 97.00 105.40 102.70 98.10 104.50 87.40 89.90 109.80 111.70 98.60 96.90 95.10 97.00 112.70 102.90 97.40 111.40 87.40 96.80 114.10 110.30 103.90 101.60 94.60 95.90 104.70 102.80 98.10 113.90 80.90 95.70 113.20 105.90 108.80 102.30 99.00 100.70 115.50
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R Code
library(MASS) (f<-fitdistr(x, 'cauchy')) xlab <- paste('Cauchy(location=',round(f$estimate[[1]],2)) xlab <- paste(xlab,', scale=') xlab <- paste(xlab,round(f$estimate[[2]],2)) xlab <- paste(xlab,')') bitmap(file='test2.png') qqplot(qcauchy(ppoints(x), location=f$estimate[[1]], scale=f$estimate[[2]]), x, main='QQ plot (Cauchy)', xlab=xlab ) grid() 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,'location',header=TRUE) a<-table.element(a,f$estimate[1]) a<-table.element(a,f$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'scale',header=TRUE) a<-table.element(a,f$estimate[2]) a<-table.element(a,f$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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1 seconds
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Big Analytics Cloud Computing Center
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