Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
100.70 97.90 96.50 96.60 96.60 95.50 91.80 89.30 87.00 85.90 88.00 87.90 89.20 90.90 91.60 90.20 89.10 87.50 86.30 86.00 84.40 86.10 91.00 92.70 88.00 84.30 82.20 80.80 79.40 80.20 82.20 82.20 81.20 82.10 88.10 88.50 92.10 98.60 100.90 100.60 101.10 102.10 103.60 102.80 108.30 104.00 106.10 106.30 109.00 111.00 113.70 112.70 110.30 114.50 119.30 121.80 125.40 129.70 129.40 134.50 141.20 141.40 152.20 167.70 173.30 168.70 172.60 169.80 172.00 179.40 174.60 172.50 172.60 176.30 178.90 179.60 179.90 180.30 180.90 177.70
Box-Cox transformation parameter
12
1
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Degree (d) of non-seasonal differencing
0
1
2
Degree (D) of seasonal differencing
0
1
2
Seasonal Period
1
2
3
4
12
Chart options
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) par3 <- as.numeric(par3) par4 <- as.numeric(par4) if (par1 == 0) { x <- log(x) } else { x <- (x ^ par1 - 1) / par1 } if (par2 > 0) x <- diff(x,lag=1,difference=par2) if (par3 > 0) x <- diff(x,lag=par4,difference=par3) bitmap(file='test1.png') r <- spectrum(x,main='Raw Periodogram') dev.off() bitmap(file='test2.png') cpgram(x,main='Cumulative Periodogram') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Raw Periodogram',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Box-Cox transformation parameter (lambda)',header=TRUE) a<-table.element(a,par1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of non-seasonal differencing (d)',header=TRUE) a<-table.element(a,par2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Degree of seasonal differencing (D)',header=TRUE) a<-table.element(a,par3) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Seasonal Period (s)',header=TRUE) a<-table.element(a,par4) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Frequency (Period)',header=TRUE) a<-table.element(a,'Spectrum',header=TRUE) a<-table.row.end(a) for (i in 1:length(r$freq)) { a<-table.row.start(a) mylab <- round(r$freq[i],4) mylab <- paste(mylab,' (',sep='') mylab <- paste(mylab,round(1/r$freq[i],4),sep='') mylab <- paste(mylab,')',sep='') a<-table.element(a,mylab,header=TRUE) a<-table.element(a,round(r$spec[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation