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Data:
43.8 60.5 190.2 144.7 240.9 210.3 219.7 176.3 199.1 109.2 78.7 67 49.9 54.3 109.7 102 134.5 211.2 174.1 207.5 108.2 113.5 68.7 23.3 63.7 72 142.3 93.5 150.1 158.7 127.9 135.5 92.3 102.5 62.4 38.5 51 57.9 133.4 110.9 112.4 199.3 124 178.3 102.1 100.7 55.7 58 69.5 94.3 187.6 152.5 170.2 226.9 237.6 242.7 177.3 101.3 53.9 59 65.9 96.6 122.5 124.9 216.3 192.7 269.3 184.9 149.1 81.5 48.7 31.3 48.1 62 121.5 127.3 188.5 196.3 274.3 199.9 144.7 102.6 65.4 48.9 43.4 89.2 71.4 133.2 179.5 166.2 119.2 184.7 79.3 103.1 48.9 62.3 50.9 66.6 99.7 103.1 185 181.3 140.1 202.3 143 79.1 65.9 41.2 41.2 66.9 172.3 180.9 144.9 190.6 133.5 151.3 110.9 118.1 70 52.4 46.4 104.9 86.2 171.7 184.9 227.9 139.7 153.7 147 94.3 41.1 46 83.1 22.8 128.3 118.1 215.4 273.4 165.1 199.5 179.5 95.5 76.8 46.5 41.7 67.9 118.7 106.9 141.9 210.3 227.5 163.7 123.7 120.2 47.1 46.9 45.1 53.9 69.4 202.5 209.4 234 150.1 132.7 124.5 84.6 57.8 51 54.7 79.3 132.9 166.6 244.1 192.9 196.7 178.3 142.5 84.9 72.3 49.5 41.2 62.4 142.7 147 235.6 170.3 97.5 185.2 143.8 102 49.3 64.1 51.5 65.7 152.6 209.1 156.1 182.4 159 144.8 64.9 111.7 31 46.6 49.9 78.7 107.2 203.3 162.9 149.8 197.6 134.8 98.5 79.3 42.9 74.7 59.5 26.3 70.9 150.5 147.3 185.9 144.5 274.9 159.9 107.3 75.4 37.9 45.7 92.9 160.2 205.2 237.1 124.2 174.7 133.7 146.4 93.7 68.6 65.4 51 115.1 112.5 182.5 233.3 242.1 262.5 210.3 151.1 125 76.2 65.4 40.6 67.5 138.8 163.7 174.1 244.5 174 171.1 112.7 96.6 56.9 55.3 48.9 58.6 92.6 200.4 152.1 251.9 216.7 174.7 110.8 105.6 75.1 69.8 94.1 96.7 105 178.2 207 217.6 194 180.5 140.3 105 72.1 77.7 42.5 75.9 140.7 183.3 223 139.7 203.4 237.4 151.7 84.1 54.4 28.4 75.7 79.7 107.9 202.4 145.9 157.1 157.1 123.5 168.8 94.5 60.1 54.5 40.1 86.3 161.4 173.7 217.5 155.3 268.3 188 153.1 119.7 71.5 47.3 50.3 78.9 149.7 158.7 246.6 145 168 161.4 94.3 116.5 77.9 18.2 50.8 83.1 110.2 168 205.6 297.1 157.9 170.5 102.6 92.9 76.4 62.3 54.6 55.4 110.7 145.2 196 145.7 188.1 119.6 118 93.7 51.8 29.5 85.8 65.5 102 153.8 228 226.3 272.7 245.6 213.9 144.2 70.6 45 37.8 82.3 78 164.9 182.3 274.9 129.7 147.1 122.8 60.9 73.4 54.5 43.6 65.1 173.2 86.9 225.2 231.2 196.5 185.7 135.8 118.2 63.4 76.5 70 70.6 126.3 143.3 177.5 280.3 137.3 154.5 142.3 108.8 32.7 72.6 58.9 66.4 85.8 119.1 193.4 199.4 188.2 142.6 129.7 78.8 60.4 49.8 37.2 57.3 65.9 128.5 190.8 156.1 214.7 217.7 210.4 134.5 55 51.1 83.7 31.1 137.7 141.6 179.6 188.7 122.8 181.2 122.9 109.9 77.4 71.9 42.5 41.5 121.5 81.5 234.9 199 149.7 188.6 168 90.4 61 41.7 64.2 88.2 174.6 130.8 184.2 232 234.4 167.1 116.5 95.1 69.2 70.6 50 54 148.5 184.5 155 206.6 136.2 124 114.9 66.5 47.9 35.9 40 78.1 70.5 221.3 161.9 276.9 243.8 157.5 97.4 112 84.6 35.6 34.5 115.9 120.8 132.7 224.8 270.9 192.4 185.6 157.3 106.2 64.7 43.8 42.1 69.5 106 122.9 228.9 143.5 259.3 134.2 166.5 135.2 102 29.8 41.8 27.3 144 117.6 141.9 150.4 168.7 160.9 129.1 91.6 80.6 47.6 38.8 74.1 150.7 167.7 168 249.5 171.1 192 153.9 95.1 89.1 62.9 56.3 58.3 101.7 142.1 191.4 206.2 187.8 198.7 146.5 105.4 52.9 58.8 44.7 57.8 72.7 131.4 159.1 301 242.4 218.6 147 120.7 85.1 34.4 70.3 42.6 107.8 148.7 172 261.4 254.2 257.4 118.2 43.6 54.1 58.6 35.4 74.4 87.2 157.9 217.5 123.2 193.6 123.4 101.8 107.3 102.4 45.2 53.6 58.9 128.1 113.6 202.8 171.7 146.4 157.4 159.3 87.5 77.3 34.3 72 67.3 92.9 126.4 190.9 166.6 192.2 167.4 171 117 70 59.7 84 58.8 86.7 165.4 228.7 186.7 168.9 169 136.4 111.8 61.4 64.4 50.9 75.3 57.8 110.4 98.3 122.8 129 199.8 157.3 101.9 43.7 57.5 55 33.8 144.7 164.4 187.2 148.4 151.4 159.8 141 66.3 68.5 60.4 54.9 74 89.5 150.5 126.8 180.3 257.5 214.5 92.4 119.7 44.3 62.9 86.1 66 48.8 236.8 143.4 244.3 249.4 199.8 99.6 88.6 53.8 57.6 51.1 78 112.4 138.3 178.3 165 216 164.9 143.3 100.8 86.1 44.2 76.4 71.2 127.3 139.6 205.6 222.7 201.2 147 171.6 119.7 77.9 64.8 68.8 67.8 111.6 158.7 168.7 129.3 179.4 158.2 132.3 109.5 43.9 42.9 47.7 103.7 85.2 132 178.1 142.3 138.8 178.8 136.9 120 91.4 46.7 68.2 107 100.9 133.9 300.8 244.4 280.4 269.5 141.6 90.8 104.1 26.5 58.3 95.7 144.1 234.4 285 121.1 268.5 236.6 164.7 124.4 83.7 58.8 66.9 60 87.2 156.6 142.9 150 217.3 241.4 165.4 79.4 57.4 58.4 46.8 67.3 73.3 139.2 262.7 212.2 164 173.6 120.2 101.3 61.5 47.2 38 54.7 135 111.9 196.7 231.4 190 238.3 107.7 120 76.3 55 87 77.6 127.6 177.7 162.1 254.9 248.3 191.8 113.1 137.5 46.7 68.2 61.8 74.9 198.7 190.1 233.5 194.4 247.6 285.1 135.3 139.9 78.1 40.9 29.3 103.4 76.4 148.3 185.7 290.7 256.6 211.6 125.3 130.8 101 55.5 51.4 64.2 150.2 189.9 261.4 137.1 231.7 172 169.7 153.8 47.1 55.7 64 113 77.5 105.8 199.8 114 157 225 133.8 94.5 66.3 38.1 51.1 81.3 97.4 147.6 153.6 202.1 235.4 159.2 155.2 144.8 81.1 60.9 82.1 104.9 112.6 143.4 189.8 164.6 161.2 209.4 126.1 83.9 69.2 51.9 83.3 85 74.1 148.2 198.3 226.8 206.1 184.1 123 100.9 86.9 79.2 44.4 80.5 101.1 210 177.5 163.3 178.8 166.2 167.1 104.8 52.3 41.3 87.7 94.4 154.8 169.8 191.2 213.6 192 228.4 175.3 134.8 78.9 53.6 62.7 79.1 101.5 150.3 195.5 223.6 169.5 194.1 174.4 102.4 52.4 58.3 65.4 66.3 79.3 136.3 226.4 177.6 192 235.7 155.4 92 88 55.7 54.9 73.1 95.5 152.5 165.7 246.2 303.7 167.2 156.5 109 101.2 42.7 79.8 67.6 165.4 210.7 165.5 149 195.1 209.2 142.6 102.5 86.9 57.2 62.4 124.1 115.2 161.2 173.2 223.8 198.5 141.8 113.5 132.2 67 73.5 69.3 64.5 161.4 168.4 226.1 203.3 212.3 190.6 163.7 109.7 73.5 61.5 68.2 59.3 130.2 209.5 207.4 230.5 181 141.7 123.1 123.5 53.6 25.8 49.3 34.2 141.5 211.4 208.7 188.5 179.4 157.8 151.7 130.6 64.8 62.6 85.7 71.7 168.1 131.8 196 123.5 181.1 162 180.4
Box-Cox transformation parameter
1
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
0
1
2
Degree (D) of seasonal differencing
0
0
1
2
Seasonal Period
1
1
2
3
4
12
Chart options
R Code
par4 <- '1' par3 <- '0' par2 <- '0' par1 <- '1' 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')
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