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Data:
404.45 387.97 390.27 384.72 371.35 367.73 375.21 365.55 361.80 366.80 394.36 409.66 410.12 416.54 393.66 374.93 368.85 352.66 361.82 394.86 389.56 381.33 381.87 378.16 384.59 363.75 363.39 358.05 357.12 366.36 368.01 356.72 348.46 358.83 359.96 361.88 354.44 353.85 344.64 338.73 337.04 340.78 352.45 343.60 345.30 344.28 334.92 334.66 328.99 329.31 329.97 341.95 367.04 371.91 392.03 379.80 355.56 364.00 373.94 383.24 387.11 381.66 384.00 377.91 381.34 385.71 385.45 380.21 391.35 390.16 384.38 379.48 378.74 376.75 381.82 391.34 385.23 387.62 386.14 383.50 382.93 383.20 385.21 387.44 398.70 404.92 396.51 392.87 391.99 385.25 383.46 387.51 383.29 380.91 377.87 369.34 355.03 346.40 352.31 344.71 344.10 340.80 323.78 324.00 322.62 324.86 306.35 288.78 289.26 297.74 295.87 308.56 298.97 292.22 292.87 284.23 288.66 296.60 294.24 291.36 287.31 287.50 286.24 282.62 276.93 261.40 256.20 256.94 264.47 311.56 293.65 283.74 284.59 300.85 286.70 279.96 275.29 285.37 282.15 274.52 273.68 270.40 265.99 271.89 265.93 262.02 263.27 260.75 272.06 270.74 267.71 272.66 282.48 283.32 276.25 275.99 281.76 295.68 294.35 302.86 314.48 321.54 313.57 310.05 318.71 316.75 319.25 333.30 356.86 359.58 341.56 328.21 355.41 356.91 350.75 358.99 378.86 379.09 390.20 407.67 414.50 404.73 405.98 404.85 383.95 391.78 398.44 400.13 405.40 420.21 439.06 442.97 424.08 423.43 434.35 429.14 422.90 430.30 424.75 437.77 455.94 470.11 476.67 509.42 549.43 555.52 557.22 611.85 676.77 597.90 633.09 631.56 600.15 586.65 626.83 629.51 630.35 665.10 655.89 680.01 668.31 655.71 665.27 664.53 710.65 754.48 808.31 803.62 887.78 924.28 971.06 912.02 889.13 889.54 941.17 840.39 824.92 812.82 757.85 819.94 857.73 939.76 925.99 892.66 926.86 947.81 934.27 949.50 996.44 1043.51 1126.12 1135.01
Sample Range:
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From:
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bandwidth of density plot
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# lags (autocorrelation function)
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Chart options
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) library(lattice) bitmap(file='pic1.png') plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(x) grid() dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1) } else { densityplot(~x,col='black',main='Density Plot') } dev.off() bitmap(file='pic4.png') qqnorm(x) qqline(x) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot1.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main='Lag plot (k=1), lowess, and regression line') lines(lowess(z)) abline(lm(z)) dev.off() if (par2 > 1) { bitmap(file='lagplotpar2.png') dum <- cbind(lag(x,k=par2),x) dum dum1 <- dum[(par2+1):length(x),] dum1 z <- as.data.frame(dum1) z mylagtitle <- 'Lag plot (k=' mylagtitle <- paste(mylagtitle,par2,sep='') mylagtitle <- paste(mylagtitle,'), and lowess',sep='') plot(z,main=mylagtitle) lines(lowess(z)) dev.off() } bitmap(file='pic5.png') acf(x,lag.max=par2,main='Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(x,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(x,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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R Server
Big Analytics Cloud Computing Center
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