Duncan Huysmans Opgave 9 opdracht 2 correct

*Unverified author*

R Software Module: rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Fri, 05 Jun 2009 11:05:40 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp.htm/, Retrieved Fri, 05 Jun 2009 19:07:35 +0200

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp.htm/}, year = {2009}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2009}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Duncan Huysmans Opgave 9 opdracht 2 correct

Dataseries X:

» Textbox « » Textfile « » CSV «

1664.81 2397.53 2840.71 3547.29 3752.96 3714.74 4349.61 3566.34 5021.82 6423.48 7600.60 19756.21 2499.81 5198.24 7225.14 4806.03 5900.88 4951.34 6179.12 4752.15 5496.43 5835.10 12600.08 28541.72 4717.02 5702.63 9957.58 5304.78 6492.43 6630.80 7349.62 8176.62 8573.17 9690.50 15151.84 34061.01 5921.10 5814.58 12421.25 6369.77 7609.12 7224.75 8121.22 7979.25 8093.06 8476.70 17914.66 30114.41 4826.64 6470.23 9638.77 8821.17 8722.37 10209.48 11276.55 12552.22 11637.39 13606.89 21822.11 45060.69 7615.03 9849.69 14558.40 11587.33 9332.56 13082.09 16732.78 19888.61 23933.38 25391.35 36024.80 80721.71 10243.24 11266.88 21826.84 17357.33 15997.79 18601.53 26155.15 28586.52 30505.41 30821.33 46634.38 104660.67

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1664.81 NA NA 0.474541560006453 NA 2 2397.53 NA NA 0.604244670194867 NA 3 2840.71 NA NA 0.982889337904476 NA 4 3547.29 NA NA 0.656813757195405 NA 5 3752.96 NA NA 0.674859893085904 NA 6 3714.74 NA NA 0.679399190357424 NA 7 4349.61 4217.04196136620 5421.13333333333 0.77788936409967 1.03143626263345 8 3566.34 4262.88612094492 5572.62125 0.764969648878419 0.836602221785245 9 5021.82 4906.7924487741 5872.00208333333 0.835625120553207 1.02344251411217 10 6423.48 5628.97648489268 6107.13416666667 0.921705063500355 1.14114528942156 11 7600.6 9247.09928421017 6249.07833333333 1.47975409987822 0.821944240717558 12 19756.21 20111.6147316978 6390.1 3.14730829434560 0.982328384048764 13 2499.81 3092.99288187021 6517.85458333333 0.474541560006453 0.808217184932047 14 5198.24 4014.29518637318 6643.49291666667 0.604244670194867 1.29493217580157 15 7225.14 6597.81873400405 6712.67708333333 0.982889337904476 1.09508010014929 16 4806.03 4405.86508506216 6707.93666666667 0.656813757195405 1.09082550355311 17 5900.88 4650.95385812665 6891.7325 0.674859893085904 1.26874619271686 18 4951.34 5072.4671075385 7466.10708333333 0.679399190357424 0.976120671663206 19 6179.12 6164.42607736116 7924.55375 0.77788936409967 1.00238366434351 20 4752.15 6148.79065783847 8037.95375 0.764969648878419 0.772859292898834 21 5496.43 6829.4150904682 8172.82166666666 0.835625120553207 0.804817092999862 22 5835.1 7657.02295425756 8307.45458333333 0.921705063500355 0.762058574834948 23 12600.08 12360.2139748687 8352.88375 1.47975409987822 1.01940630037789 24 28541.72 26586.9156668105 8447.50916666667 3.14730829434560 1.07352505110737 25 4717.02 4065.04519746698 8566.2575 0.474541560006453 1.16038562201948 26 5702.63 5291.80236006703 8757.71458333333 0.604244670194867 1.07763472858192 27 9957.58 8874.11303805545 9028.59833333333 0.982889337904476 1.12209298634108 28 5304.78 6119.82113180836 9317.4375 0.656813757195405 0.866819452030696 29 6492.43 6468.12884644227 9584.4025 0.674859893085904 1.00375706083392 30 6630.8 6740.11300003194 9920.69625 0.679399190357424 0.983781725910023 31 7349.62 7935.12234791794 10200.8366666667 0.77788936409967 0.926213822264307 32 8176.62 7845.277235125 10255.67125 0.764969648878419 1.04223467889592 33 8573.17 8659.57372351028 10362.98875 0.835625120553207 0.990022173577009 34 9690.5 9687.135195096 10510.01625 0.921705063500355 1.00034734777994 35 15151.84 15686.7542159168 10600.9195833333 1.47975409987822 0.96590026154843 36 34061.01 33588.691776509 10672.19625 3.14730829434560 1.01406182255128 37 5921.1 5091.40108330613 10729.0941666667 0.474541560006453 1.16296082416573 38 5814.58 6497.45527526742 10753.0204166667 0.604244670194867 0.894901119540324 39 12421.25 10541.2837899507 10724.7920833333 0.982889337904476 1.17834319305980 40 6369.77 6997.83334208325 10654.2125 0.656813757195405 0.910248885421973 41 7609.12 7233.657853314 10718.755 0.674859893085904 1.05190488053205 42 7224.75 7248.80266974121 10669.4308333333 0.679399190357424 0.996681842390108 43 8121.22 8136.2456430059 10459.3866666667 0.77788936409967 0.998153246145066 44 7979.25 7987.12683206594 10441.1029166667 0.764969648878419 0.99901380906657 45 8093.06 8650.79652615027 10352.485 0.835625120553207 0.935527725745912 46 8476.7 9529.22292296048 10338.69 0.921705063500355 0.889547874840408 47 17914.66 15518.5024753754 10487.2170833333 1.47975409987822 1.15440649176212 48 30114.41 33543.9055794804 10657.96625 3.14730829434560 0.897760993532657 49 4826.64 5179.05266622668 10913.8020833333 0.474541560006453 0.93195422233784 50 6470.23 6789.18107727692 11235.8145833333 0.604244670194867 0.953020684873992 51 9638.77 11375.9960075705 11574.0354166667 0.982889337904476 0.847290205937628 52 8821.17 7839.38335764463 11935.47375 0.656813757195405 1.12523773842466 53 8722.37 8308.90340402749 12312.0420833333 0.674859893085904 1.04976187300145 54 10209.48 8898.50846044726 13097.6141666667 0.679399190357424 1.14732486296775 55 11276.55 10763.3118873652 13836.55875 0.77788936409967 1.04768403238758 56 12552.22 10781.1399073746 14093.5525 0.764969648878419 1.16427577304826 57 11637.39 12065.8818435743 14439.3479166667 0.835625120553207 0.964487316457315 58 13606.89 13603.9880701016 14759.5891666667 0.921705063500355 1.00021331464593 59 21822.11 22048.7362383567 14900.2704166667 1.47975409987822 0.989721576969004 60 45060.69 47352.4715590151 15045.3870833333 3.14730829434560 0.95160164858219 61 7615.03 7304.34398770277 15392.4220833333 0.474541560006453 1.04253441689223 62 9849.69 9622.86702411178 15925.4479166667 0.604244670194867 1.02357124704310 63 14558.4 16456.9719994651 16743.46375 0.982889337904476 0.884634184251708 64 11587.33 11656.3527857466 17746.8158333333 0.656813757195405 0.994078526361095 65 9332.56 12707.3511221739 18829.61375 0.674859893085904 0.734422139616101 66 13082.09 14204.3811782521 20907.2683333333 0.679399190357424 0.92098978729391 67 16732.78 17504.5743679014 22502.6529166667 0.77788936409967 0.955908989748606 68 19888.61 17342.7885095610 22671.21125 0.764969648878419 1.14679424182769 69 23933.38 19247.0474095281 23033.1125 0.835625120553207 1.24348319463026 70 25391.35 21730.4695930960 23576.3808333333 0.921705063500355 1.16846761599975 71 36024.8 35653.9579723915 24094.5154166667 1.47975409987822 1.01040114614752 72 80721.71 77430.7395922322 24602.21 3.14730829434560 1.04250211770027 73 10243.24 11970.2090224530 25224.7854166667 0.474541560006453 0.855727747175202 74 11266.88 15698.1539203483 25979.7970833333 0.604244670194867 0.717720061681623 75 21826.84 26160.6264381485 26616.0445833333 0.982889337904476 0.834339347783018 76 17357.33 17810.2461312094 27116.1283333333 0.656813757195405 0.97456991173099 77 15997.79 18750.6064573847 27784.4433333333 0.674859893085904 0.853187870822144 78 18601.53 19854.7387261997 29223.9658333333 0.679399190357424 0.936881127297535 79 26155.15 NA NA 0.77788936409967 NA 80 28586.52 NA NA 0.764969648878419 NA 81 30505.41 NA NA 0.835625120553207 NA 82 30821.33 NA NA 0.921705063500355 NA 83 46634.38 NA NA 1.47975409987822 NA 84 104660.67 NA NA 3.14730829434560 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/198021244221538.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/198021244221538.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/2hnzl1244221538.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/2hnzl1244221538.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/3c34a1244221538.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/3c34a1244221538.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/4hf2c1244221538.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244221650wyveuu5hkjkzitp/4hf2c1244221538.ps (open in new window)

Parameters (Session):

par1 = 9 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2) x <- ts(x,freq=par2) m <- decompose(x,type=par1) m$figure bitmap(file='test1.png') plot(m) dev.off() mylagmax <- length(x)/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend') acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend') spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal') spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend') cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal') cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observations',header=TRUE) a<-table.element(a,'Fit',header=TRUE) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Random',header=TRUE) a<-table.row.end(a) for (i in 1:length(m$trend)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i]) a<-table.element(a,m$trend[i]) a<-table.element(a,m$seasonal[i]) a<-table.element(a,m$random[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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