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Data:
15086 20559 39383 68032 42346 40184 29183 18049 24377 48033 61410 40637 37914 22481 17061 21921 34043 36152 38929 36713 27928 14178 19331 35030 37834 45257 39650 33001 22268 34283 63733 54548 31666 32654 28409 16234 19544 33375 30839 27581 28596 28542 14285 20799 28729 30278 31266 38341 24938 15700 17382 34229 29584 33909 29397 24644 14124 18770 32681 30518 34310 24217 15806 12362 13751 25312 23549 30305 30411 15593 17382 15806 29183 33348 33589 30198 23469 15593 16474 27341 26673 33268 26406 23656 15086 18316 27528 30305 34550 34710 23843 12362 21200 27261 31586 33322 32814 21974 17115 14445 26673 31746 28249 29103 21974 17622 21066 28382 32147 35885 40824 28622 24297 30465 47927 51665 57058 48407 30011 21413 30518 41171 37487 44456 41465 28409 34870 29557 44936 44028 45310 39302 28516 19865 30091 38101 44402 52359 71182 60796 43735 63947 89071 86321 90967 54441 36339 29290 65842 99404 83865 84452 76309 69554 44616 67337 94144 84425 76763 73559 60956 46271 74066 91634 63947 56017 53293 54895 48781 60449 99965 84746 81088 77777 60315 46218 62985 92596 78525 72811 62318 48140 45443 66910 90032 91661 103516 100285 72384 51985 72224 99351 108616 102128 97669 71716 51584 63413 88137 86535 91955 84853 54388 40931 58900 76576 80447 60315 52012 37487 19972 25338 23549 19785 29637 34416 26914 25071 24003 19358 28783 46992 49796 40904 33722 42640 56097 62184 63039 61730 44349 32307 45123 63466 71903 73211 67845 51237 31506 45043 74386 76602 72704 71770 52225 40958 55856 79700 81889 82049 66643 54655 36739 53026 78098 81248 84372 75614 63012 38795 55670 81168 85787 88591 75401 63413 42907 62291 86241 85200 84559 75801 72304 50944 70034 104691 88404 93397 88030 60582 50890 69847 90166 84158 82503 83811 66296 42640 55563 82450 84799 82370 83384 60075 41091 55589 79513 87656 74760 64214 47019 34229 45150 64187 73879 76175 83785 52786 43681 61864 74573 79913 78765 79112 62718 40557 57058 88804 89205 82904 78445 62825 57832 70675 102795 107094 105625 98390 74360 64641 82423 116759 101941 101140 98790 65949 49635 77323 109203 102902 93637 89365 72250 53267 73238 99725 69100 66323 80447 80954 48194 52546 91821 84372 90994 72410 62745 47366 63947 82690 89712 79085 80527 61303 40691 58340 79166 82850 82076 73292 60823 51157 61410 64294 67658 66323 66563 52145 36980 50703 68112 68379 65735 60716 50463 33749 39436 66990 70541 75027 69233 53213 31186 41145 67604 68699 71690 60022 51718 32814 42400 71316 70141 64694 60636 37620 35431 41145 69393 72891 62638 63439 54014 37567 38875 64854 75214 72944 71796 60689 53000 50757 71289 75080 77377 68779 49155 30678 49342 67604 63733 71209 59461 49609 30839 39302 67685 67925 66056 60743 49422 30972 34924 56818 62024 59274 59007 43494 26486 41252 63146 70114 57779 61944 48728 32708 40237 67845 68913 66697 68272 51317 30812 37300 63599 72918 74386 73292 56577 41652 58900 86188 88350 85787 86535 67978 42720 64187 98897 108429 92249 111820 77163 59648 83651 103569 108749 96948 90113 75614 52733 78178 103302 96040 98843 93183 75267 54815 93904 110725 107735 100793 102795 73772 63092 82476 162042 108215 100846 104183 82156 59728 97028 148746 101380 100953 100205 73292 57138 63039 135236 104370 109844 104290 78231 58153 88938 132459 107654 113021 117587 85387 64347 88778 130777 159185 139988 136731 90273 61277 81275 82503 74333 77350 102662 76923 62291 97455 127733 101861 87763 80954 72918 67952 96574 148105 151576 132592 117213 102982 92622 114196 145515 157664 129522 121886 99271 76923 103649 111232 123621 104077 112354 69260 47286 66910 78738 62905 44082 25392 31666 30732 35751 47579 44002 30064 28809 44375 39249 48007 73452 91154 71342 63226 58820 50623 63573 75347 80714 88644 82370 63439 44776 62024 86081 95212 88244 80287 61330 47206 64400 89579 97722 109203 120551 80234 52679 76923 99164 100499 101620 94385 75241 58420 72677 76148 70568 76469 71449 49368 33135 62131 77003 81836 75107 112968 84399 65015 83758 116225 104984 115451 115718 82930 61170 88377 118254 124208 124502 109871 81782 59034 79593 117667 107788 108135 104958 78685 57378 76496 104370 102875 99591 97802 79299 57138 78738 123007 117293 147731 156409 85173 66430 85387 123728 114703 113769 96307 79433 58607 75828 108429 104157 99538 90353 69874 53694 66910 102261 104584 109550 99858 83598 64748 86642 84719 79566 93236 81649 61891 44723 62291 78365 127493 123568 114356 88911 63092 85574 115104 115638 107975 117533 80474 58259 78231 70408 73986 78471 83037 52813 34123 45791 64454 61196 63039 59781 50997 31346 37861 53614 66857 73478 82183 51531 35564 42346 75054 81088 76255 71503 57992 46298 58313 92943 97055 93664 79993 67364 53106 63813 87843 95239 91661 85947 70408 47152 56043 79753 82530 76148 71583 59060 38582 54521 81702 81755 77136 64748 51932 34683 39730 68325 71049 68779 72758 51878 35484 47499 68405 77350 59461 67578 56524 35030 41839 68112 61570 76335 68432 46832 36766 42320 66563 67498 71903 63813 53000 32467 41065 64187 69740 68539 59327 49876 35111 48487 71503 68726 66803 65735 54068 30732 47606 72117 80207 77136 67231 54468 39169 53000 78551 76148 78738 74119 54602 41679 52279 79379 90219 83571 86081 58019 41465 56871 83090 96280 94091 97161 70141 50303 66002 84746 88404 119936 97669 78712 59114 85200 101380 103382 111713 106373 75134 63012 77056 100712 117800 118254 102448 79272 68592 93877 133206 147571 144687 111846 87069 65976 95880 150828 128614 122526 105946 82984 66216 98897 128080 140122 125223 122473 85467 66350 86722 106266 123381 128294 117080 84292 70007 101647 151336 149200 143646 106319 78284 58553 88564 114303 120337 123354 117133 101674 60876 87816 118495 114169 117720 120871 84826 64774 91955 115184 103783 96948 89979 84933 72143 87896 122286 131631 132806 139508 102074 74466 104717 132272 130323 138066 119990 102261 78605 104584 127599 111579 123381 103890 61811 47366 53507 75614 60262 47980 28703 20986 29290 37594 48888 50757 56417 30465 30411 38822 50383 73051 68325 84078 93477 72090 56177 77243 102181 93877 90433 88617 65655 67177 62665 95212 103543 109871 105305 78738 56898 109497 168344 123915 120711 113128 83838 67151 85574 116999 136117 127065 111473 80100 74093 102021 146690 150508 135289 116012 78498 59701 86294 107468 115371 118388 110485 100659 79139 109310 139935 126051 141270 118949 97455 77777 107040 149760 147731 159132 124369 98016 73185 102528 242516 293460 320987 268736 239873 189143 248550 269670 278801 272634 181240 90566 67017 92809 134755 137291 138199 125704 107414 75588 100606 120791 124075 101460 105198 70007 58446 70808 101220 127599 120497 110752 90113 70541 84559 120524 118922 123648 113448 84132 65228 101460 125303 141029 130136 124502 97241 71556 97188 141430 134621 134354 113261 74520 70835 87736 128908 118575 118014 111232 79593 56043 81221 115024 91661 110298 99591 70488 50757 69473 117186 82637 91207 76682 66964 44536 64267 99458 89338 104397 90486 70702 58633 68672 93477 110485 155875 86828 74653 57512 88484 78979 84158 76389 77136 55189 36686 50703 75428 78979 78151 69260 56844 39436 51985 73585 67177 65442 61757 50890 29050 48647 70488 63199 62825 66803 49555 30892 40103 59434 67604 70194 63760 53106 34310 44883 68058 74333 71156 67337 52279 37727 43254 74493 77991 68699 66483 62318 35885 49902 78231 67044 71476 68112 52492 41492 46805 69847 73478 78632 74813 60182 41305 39116 72010 79246 71690 69420 57939 46298 60422 81035 82637 79726 86348 66296 33695 52199 72517 72277 73078 76763 65655 34657 56417 68699 77163 79700 78151 59781 44829 46992 77030 92596 84933 83918 63306 47286 77403 102768 118361 107708 94705 76122 45417 79806 106346 95826 93797 99351 83838 54174 84559 116492 114543 123407 114677 110378 96040 141857 233465 146022 142124 118067 83010 75695 104157 150161 174832 139935 108749 109977 78872 126451 161295
Seasonal period
12
12
1
2
3
4
5
6
7
8
9
10
11
12
Seasonal window
(?)
Seasonal degree
(?)
0
0
1
Trend window
(?)
Trend degree
(?)
1
1
0
Low-pass window
(?)
Low-pass degree
(?)
1
1
0
Robust loess fitting
FALSE
FALSE
TRUE
Chart options
Title:
R Code
par1 <- as.numeric(par1) #seasonal period if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window par3 <- as.numeric(par3) #s.degree if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window par5 <- as.numeric(par5)#t.degree if (par6 != '') par6 <- as.numeric(par6)#l.window par7 <- as.numeric(par7)#l.degree if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust nx <- length(x) x <- ts(x,frequency=par1) if (par6 != '') { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8) } else { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8) } m$time.series m$win m$deg m$jump m$inner m$outer bitmap(file='test1.png') plot(m,main=main) dev.off() mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend') acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Component',header=TRUE) a<-table.element(a,'Window',header=TRUE) a<-table.element(a,'Degree',header=TRUE) a<-table.element(a,'Jump',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,m$win['s']) a<-table.element(a,m$deg['s']) a<-table.element(a,m$jump['s']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,m$win['t']) a<-table.element(a,m$deg['t']) a<-table.element(a,m$jump['t']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Low-pass',header=TRUE) a<-table.element(a,m$win['l']) a<-table.element(a,m$deg['l']) a<-table.element(a,m$jump['l']) 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,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observed',header=TRUE) a<-table.element(a,'Fitted',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,'Remainder',header=TRUE) a<-table.row.end(a) for (i in 1:nx) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]+m$time.series[i,'remainder']) a<-table.element(a,m$time.series[i,'seasonal']) a<-table.element(a,m$time.series[i,'trend']) a<-table.element(a,m$time.series[i,'remainder']) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Raw Output
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Computing time
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R Server
Big Analytics Cloud Computing Center
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