Bouwvergunningen

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 19 May 2008 15:42:22 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn.htm/, Retrieved Mon, 19 May 2008 23:43:03 +0200

User-defined keywords:

Dataseries X:

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2434 2637 1831 1851 1839 2609 2417 2394 2372 2717 2998 2538 3007 2475 2175 2465 2279 2323 2746 2601 2486 2718 2646 2551 2712 2606 2365 3533 3509 2912 3599 2719 2869 4085 2686 2545 3071 3388 2652 3190 2884 3295 3818 3226 3953 3810 2877 3515 3708 3450 3360 4098 4374 3703 4257 3487 3659 3904 2957 3320 3420 3500 2791 2919 3179 3016 3492 3034 2612 3525 2846 3212 2591

Text written by user:

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 2434 NA NA 92.8046875 NA 2 2637 NA NA -82.4973958333331 NA 3 1831 NA NA -449.0390625 NA 4 1851 NA NA 208.690104166667 NA 5 1839 NA NA 136.752604166667 NA 6 2609 NA NA -74.2161458333334 NA 7 2417 2870.37760416667 2410.29166666667 460.0859375 -453.377604166667 8 2394 2275.7734375 2427.41666666667 -151.643229166667 118.226562500000 9 2372 2499.76302083333 2435 64.7630208333335 -127.763020833333 10 2717 2916.03385416667 2474.91666666667 441.1171875 -199.033854166667 11 2998 2108.09635416667 2518.83333333333 -410.736979166667 889.903645833334 12 2538 2289.16927083333 2525.25 -236.080729166667 248.830729166667 13 3007 2619.84635416667 2527.04166666667 92.8046875 387.153645833333 14 2475 2466.87760416667 2549.375 -82.4973958333331 8.12239583333348 15 2175 2113.7109375 2562.75 -449.0390625 61.2890625 16 2465 2776.23177083333 2567.54166666667 208.690104166667 -311.231770833333 17 2279 2689.66927083333 2552.91666666667 136.752604166667 -410.669270833333 18 2323 2464.57552083333 2538.79166666667 -74.2161458333334 -141.575520833333 19 2746 2987.12760416667 2527.04166666667 460.0859375 -241.127604166667 20 2601 2368.56510416667 2520.20833333333 -151.643229166667 232.434895833333 21 2486 2598.34635416667 2533.58333333333 64.7630208333335 -112.346354166667 22 2718 3027.1171875 2586 441.1171875 -309.1171875 23 2646 2271.01302083333 2681.75 -410.736979166667 374.986979166667 24 2551 2521.4609375 2757.54166666667 -236.080729166667 29.5390625 25 2712 2910.4296875 2817.625 92.8046875 -198.429687500000 26 2606 2775.5859375 2858.08333333333 -82.4973958333331 -169.5859375 27 2365 2429.91927083333 2878.95833333333 -449.0390625 -64.9192708333335 28 3533 3160.56510416667 2951.875 208.690104166667 372.434895833333 29 3509 3147.25260416667 3010.5 136.752604166667 361.747395833333 30 2912 2937.70052083333 3011.91666666667 -74.2161458333334 -25.700520833333 31 3599 3486.7109375 3026.625 460.0859375 112.2890625 32 2719 2922.5234375 3074.16666666667 -151.643229166667 -203.523437500000 33 2869 3183.47135416667 3118.70833333333 64.7630208333335 -314.471354166666 34 4085 3557.4921875 3116.375 441.1171875 527.5078125 35 2686 2665.3046875 3076.04166666667 -410.736979166667 20.6953125000005 36 2545 2829.87760416667 3065.95833333333 -236.080729166667 -284.877604166667 37 3071 3183.84635416667 3091.04166666667 92.8046875 -112.846354166667 38 3388 3038.79427083333 3121.29166666667 -82.4973958333331 349.205729166667 39 2652 2738.54427083333 3187.58333333333 -449.0390625 -86.544270833333 40 3190 3429.98177083333 3221.29166666667 208.690104166667 -239.981770833333 41 2884 3354.54427083333 3217.79166666667 136.752604166667 -470.544270833333 42 3295 3191.95052083333 3266.16666666667 -74.2161458333334 103.049479166667 43 3818 3793.2109375 3333.125 460.0859375 24.7890624999995 44 3226 3210.60677083333 3362.25 -151.643229166667 15.3932291666665 45 3953 3459.09635416667 3394.33333333333 64.7630208333335 493.903645833333 46 3810 3902.78385416667 3461.66666666667 441.1171875 -92.7838541666665 47 2877 3150.84635416667 3561.58333333333 -410.736979166667 -273.846354166666 48 3515 3404.5859375 3640.66666666667 -236.080729166667 110.414062500000 49 3708 3768.76302083333 3675.95833333333 92.8046875 -60.763020833333 50 3450 3622.62760416667 3705.125 -82.4973958333331 -172.627604166667 51 3360 3254.7109375 3703.75 -449.0390625 105.2890625 52 4098 3904.10677083333 3695.41666666667 208.690104166667 193.893229166667 53 4374 3839.41927083333 3702.66666666667 136.752604166667 534.580729166667 54 3703 3623.65885416667 3697.875 -74.2161458333334 79.3411458333335 55 4257 4137.8359375 3677.75 460.0859375 119.164062500000 56 3487 3516.19010416667 3667.83333333333 -151.643229166667 -29.190104166667 57 3659 3710.97135416667 3646.20833333333 64.7630208333335 -51.971354166667 58 3904 4014.4921875 3573.375 441.1171875 -110.4921875 59 2957 3063.72135416667 3474.45833333333 -410.736979166667 -106.721354166667 60 3320 3159.9609375 3396.04166666667 -236.080729166667 160.039062500000 61 3420 3428.34635416667 3335.54166666667 92.8046875 -8.34635416666652 62 3500 3202.29427083333 3284.79166666667 -82.4973958333331 297.705729166667 63 2791 2773.25260416667 3222.29166666667 -449.0390625 17.7473958333335 64 2919 3371.56510416667 3162.875 208.690104166667 -452.565104166666 65 3179 3279.2109375 3142.45833333333 136.752604166667 -100.210937500000 66 3016 3059.1171875 3133.33333333333 -74.2161458333334 -43.1171875 67 3492 3554.37760416667 3094.29166666667 460.0859375 -62.3776041666665 68 3034 NA NA -151.643229166667 NA 69 2612 NA NA 64.7630208333335 NA 70 3525 NA NA 441.1171875 NA 71 2846 NA NA -410.736979166667 NA 72 3212 NA NA -236.080729166667 NA 73 2591 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/1z46s1211233340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/1z46s1211233340.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/2rws11211233340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/2rws11211233340.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/35t4z1211233340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/35t4z1211233340.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/4hvak1211233340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t1211233379pfx08mpau8b69jn/4hvak1211233340.ps (open in new window)

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; 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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