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Data:
0.000932570857569672 -0.0203108132423796 -0.00740244612633771 -1.96033134748516e-05 -0.00247881764132503 -0.0146429032316652 0.0287802927882739 0.00594440465345073 -0.000897153835221304 -0.00951757054790946 -0.0241105236250305 -0.0589548761565316 -0.0420482633527937 -0.0129245022944874 -0.0113315850945459 0.00969282890644101 0.0269228615266862 -0.033884634433504 0.00201252269547786 -0.0158623247635957 0.0124029812255415 -0.00776916837322891 -0.0511034038698992 -0.0164172487867153 0.0056627622655232 -0.0120137269820571 -0.00697278891520728 0.0207359633137815 -0.0138840933777682 0.0397600532401993 -0.0427967011101542 -0.0277811687963104 0.00503662630159267 0.0419179044976309 -0.00673512776792989 -0.0156255241231228 -0.0399042366063093 -0.0173247987163668 -0.000710268473735139 0.0287363751687132 0.000684917014274644 -0.00155611412861989 0.00332444680332711 0.0120325090465468 0.00199036648555317 -0.0342259467738315 -0.00181262310294394 0.0165251149934844 0.00970318330896758 0.0112580883625287 -0.00982084710598352 0.00574564877263328 0.0114333581744234 0.0255628954122663 -0.0122796621201001 0.0142475508072675 -4.92031778172031e-05 -0.0043443413456008 0.0248666984502987 -0.00462132452957265 -0.0165351836829477 -0.0100958035742273 0.00421955283508779 -0.00138733237024991 0.014498826561709 0.00616911500795214 0.00983736219357201 0.00333293068329388 -0.00309797659764033 -0.0149452729497809 0.00544968655455402 -0.034913162902699 -0.00631236324030271 0.00852428739481215 0.0239021114326191 0.00385099613737172 0.0132953006371123 -0.0211503383719361 0.0370522063722721 0.0040431049896249 0.00396756889555894 0.0193514652617433 -0.0140164522257322 0.00980197078400991 0.0284875706243669 0.031226926945389 0.00505473193057737 -0.00642775145836849 0.00751759465195623 -0.0102758924973265 0.0143298473469305 -0.0182211946052994 0.0179499970395537 0.031881851751381 0.0237215451172941 -0.000492108298878247 0.0394760583230769 -0.0289101623259483 0.0154723628260992 0.000284990762423165 -0.0190645780502774 -0.00103978895298851 0.00653817353187347 -0.00149135114799215 -0.00404516415219935 -0.000567079274514604 -0.0308987041721338 0.0141224291804049 -0.0454145615241273 0.00850159262841277 0.00157602326438588 0.0195212065399589 -0.0269517592650709 -0.00288201347647787 -0.0583284018660938 0.01469918825709 -0.0130466955013708 -0.0301970899241644 -0.000406211254377453 0.00144045073926935 -0.00253136472298887
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Seasonal Period
0
12
4
6
12
Chart options
R Code
par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) arr <- array(NA,dim=c(par1,np)) j <- 0 k <- 1 for (i in 1:(np*par1)) { j = j + 1 arr[j,k] <- x[i] if (j == par1) { j = 0 k=k+1 } } arr arr.mean <- array(NA,dim=np) arr.sd <- array(NA,dim=np) arr.range <- array(NA,dim=np) for (j in 1:np) { arr.mean[j] <- mean(arr[,j],na.rm=TRUE) arr.sd[j] <- sd(arr[,j],na.rm=TRUE) arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) } arr.mean arr.sd arr.range (lm1 <- lm(arr.sd~arr.mean)) (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) (lm2 <- lm(arr.range~arr.mean)) bitmap(file='test1.png') plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') dev.off() bitmap(file='test2.png') plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Section',header=TRUE) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,'Standard Deviation',header=TRUE) a<-table.element(a,'Range',header=TRUE) a<-table.row.end(a) for (j in 1:np) { a<-table.row.start(a) a<-table.element(a,j,header=TRUE) a<-table.element(a,arr.mean[j]) a<-table.element(a,arr.sd[j] ) a<-table.element(a,arr.range[j] ) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lnlm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Lambda',header=TRUE) a<-table.element(a,1-lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab')
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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