R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(112,118,132,129,121,135,148,148,136,119,104,118,115,126,141,135,125,149,170,170,158,133,114,140,145,150,178,163,172,178,199,199,184,162,146,166,171,180,193,181,183,218,230,242,209,191,172,194,196,196,236,235,229,243,264,272,237,211,180,201,204,188,235,227,234,264,302,293,259,229,203,229,242,233,267,269,270,315,364,347,312,274,237,278,284,277,317,313,318,374,413,405,355,306,271,306,315,301,356,348,355,422,465,467,404,347,305,336,340,318,362,348,363,435,491,505,404,359,310,337,360,342,406,396,420,472,548,559,463,407,362,405,417,391,419,461,472,535,622,606,508,461,390,432)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '6'
> main = 'Seasonal Decomposition by Loess'
> par8 <- 'FALSE'
> par7 <- '1'
> par6 <- ''
> par5 <- '1'
> par4 <- ''
> par3 <- '0'
> par2 <- 'periodic'
> par1 <- '6'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Decomposition by Loess (v1.0.2) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_decomposeloess.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1) #seasonal period
> if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
> par3 <- as.numeric(par3) #s.degree
> if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
> par5 <- as.numeric(par5)#t.degree
> if (par6 != '') par6 <- as.numeric(par6)#l.window
> par7 <- as.numeric(par7)#l.degree
> if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
> nx <- length(x)
> x <- ts(x,frequency=par1)
> if (par6 != '') {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
+ } else {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
+ }
> m$time.series
Time Series:
Start = c(1, 1) 
End = c(24, 6) 
Frequency = 6 
            seasonal    trend   remainder
 1.000000  21.634496 104.3692 -14.0036790
 1.166667  16.074666 111.2397  -9.3143376
 1.333333   7.264947 118.1102   6.6248941
 1.500000 -14.586197 123.9893  19.5968635
 1.666667 -31.478950 129.8685  22.6104414
 1.833333   1.091013 132.3318   1.5771914
 2.000000  21.634496 134.7951  -8.4295785
 2.166667  16.074666 132.3594  -0.4340336
 2.333333   7.264947 129.9237  -1.1885983
 2.500000 -14.586197 126.1948   7.3914412
 2.666667 -31.478950 122.4659  13.0130891
 2.833333   1.091013 122.1423  -5.2333431
 3.000000  21.634496 121.8188 -28.4532951
 3.166667  16.074666 125.9114 -15.9860695
 3.333333   7.264947 130.0040   3.7310465
 3.500000 -14.586197 137.0168  12.5694021
 3.666667 -31.478950 144.0296  12.4493662
 3.833333   1.091013 147.2129   0.6960843
 4.000000  21.634496 150.3962  -2.0307175
 4.166667  16.074666 149.2020   4.7232913
 4.333333   7.264947 148.0079   2.7271905
 4.500000 -14.586197 145.3263   2.2599398
 4.666667 -31.478950 142.6447   2.8342975
 4.833333   1.091013 144.4716  -5.5625830
 5.000000  21.634496 146.2985 -22.9329833
 5.166667  16.074666 153.7000 -19.7746946
 5.333333   7.264947 161.1016   9.6334844
 5.500000 -14.586197 168.8745   8.7117225
 5.666667 -31.478950 176.6474  26.8315691
 5.833333   1.091013 179.1531  -2.2440680
 6.000000  21.634496 181.6587  -4.2932250
 6.166667  16.074666 179.3124   3.6129733
 6.333333   7.264947 176.9660  -0.2309381
 6.500000 -14.586197 173.7876   2.7985991
 6.666667 -31.478950 170.6092   6.8697447
 6.833333   1.091013 171.0783  -6.1692935
 7.000000  21.634496 171.5474 -22.1818516
 7.166667  16.074666 177.6677 -13.7424081
 7.333333   7.264947 183.7881   1.9469258
 7.500000 -14.586197 192.8671   2.7190884
 7.666667 -31.478950 201.9461  12.5328595
 7.833333   1.091013 206.3964  10.5126193
 8.000000  21.634496 210.8466  -2.4811408
 8.166667  16.074666 209.3659  16.5594776
 8.333333   7.264947 207.8851  -6.1500137
 8.500000 -14.586197 203.0393   2.5469194
 8.666667 -31.478950 198.1935   5.2854608
 8.833333   1.091013 199.7947  -6.8856836
 9.000000  21.634496 201.3959 -27.0303478
 9.166667  16.074666 210.0458 -30.1205097
 9.333333   7.264947 218.6958  10.0392188
 9.500000 -14.586197 228.8562  20.7300272
 9.666667 -31.478950 239.0165  21.4624440
 9.833333   1.091013 241.3395   0.5694880
10.000000  21.634496 243.6625  -1.2969878
10.166667  16.074666 237.2572  18.6681458
10.333333   7.264947 230.8519  -1.1168303
10.500000 -14.586197 221.2872   4.2989938
10.666667 -31.478950 211.7225  -0.2435737
10.833333   1.091013 208.4924  -8.5834463
11.000000  21.634496 205.2623 -22.8968388
11.166667  16.074666 213.0916 -41.1662833
11.333333   7.264947 220.9209   6.8141625
11.500000 -14.586197 234.9597   6.6264810
11.666667 -31.478950 248.9985  16.4804079
11.833333   1.091013 255.7037   7.2052596
12.000000  21.634496 262.4089  17.9565915
12.166667  16.074666 258.6110  18.3143327
12.333333   7.264947 254.8131  -3.0780357
12.500000 -14.586197 246.8328  -3.2466275
12.666667 -31.478950 238.8526  -4.3736109
12.833333   1.091013 238.4704 -10.5613975
13.000000  21.634496 238.0882 -17.7227039
13.166667  16.074666 248.9874 -32.0620280
13.333333   7.264947 259.8865  -0.1514617
13.500000 -14.586197 277.0861   6.5001198
13.666667 -31.478950 294.2856   7.1933098
13.833333   1.091013 303.1438  10.7651426
14.000000  21.634496 312.0020  30.3634555
14.166667  16.074666 308.0782  22.8471172
14.333333   7.264947 304.1544   0.5806692
14.500000 -14.586197 294.2986  -5.7123991
14.666667 -31.478950 284.4428 -15.9638589
14.833333   1.091013 283.4032  -6.4941638
15.000000  21.634496 282.3635 -19.9979886
15.166667  16.074666 294.5672 -33.6418723
15.333333   7.264947 306.7709   2.9641344
15.500000 -14.586197 325.4703   2.1158659
15.666667 -31.478950 344.1697   5.3092059
15.833333   1.091013 352.6359  20.2730905
16.000000  21.634496 361.1020  30.2634552
16.166667  16.074666 354.2244  34.7009736
16.333333   7.264947 347.3467   0.3883824
16.500000 -14.586197 333.4287 -12.8424651
16.666667 -31.478950 319.5107 -17.0317043
16.833333   1.091013 316.7618 -11.8528321
17.000000  21.634496 314.0130 -20.6474798
17.166667  16.074666 327.5786 -42.6532986
17.333333   7.264947 341.1443   7.5907729
17.500000 -14.586197 363.6797  -1.0935245
17.666667 -31.478950 386.2152   0.2637865
17.833333   1.091013 397.4129  23.4960616
18.000000  21.634496 408.6107  34.7548167
18.166667  16.074666 400.8565  50.0688713
18.333333   7.264947 393.1022   3.6328163
18.500000 -14.586197 374.3419 -12.7556707
18.666667 -31.478950 355.5815 -19.1025492
18.833333   1.091013 346.0316 -11.1226429
19.000000  21.634496 336.4818 -18.1162564
19.166667  16.074666 345.4942 -43.5688934
19.333333   7.264947 354.5067   0.2283601
19.500000 -14.586197 376.9549 -14.3687317
19.666667 -31.478950 399.4032  -4.9242151
19.833333   1.091013 411.7295  22.1794395
20.000000  21.634496 424.0559  45.3095741
20.166667  16.074666 415.8546  73.0707255
20.333333   7.264947 407.6533 -10.9182328
20.500000 -14.586197 387.8454 -14.2591832
20.666667 -31.478950 368.0375 -26.5585251
20.833333   1.091013 362.6354 -26.7264360
21.000000  21.634496 357.2334 -18.8678667
21.166667  16.074666 373.3996 -47.4742703
21.333333   7.264947 389.5658   9.1692166
21.500000 -14.586197 417.7686  -7.1824500
21.666667 -31.478950 445.9715   5.5074919
21.833333   1.091013 460.7861  10.1228955
22.000000  21.634496 475.6007  50.7647793
22.166667  16.074666 468.5592  74.3661771
22.333333   7.264947 461.5176  -5.7825347
22.500000 -14.586197 442.2564 -20.6702156
22.666667 -31.478950 422.9952 -29.5162881
22.833333   1.091013 415.3248 -11.4158397
23.000000  21.634496 407.6544 -12.2889112
23.166667  16.074666 423.7835 -48.8581565
23.333333   7.264947 439.9126 -28.1775114
23.500000 -14.586197 469.4085   6.1777029
23.666667 -31.478950 498.9044   4.5745256
23.833333   1.091013 515.1549  18.7540824
24.000000  21.634496 531.4054  68.9601193
24.166667  16.074666 515.0193  74.9060738
24.333333   7.264947 498.6331   2.1019188
24.500000 -14.586197 479.0972  -3.5110489
24.666667 -31.478950 459.5614 -38.0824082
24.833333   1.091013 436.6314  -5.7223640
> m$win
   s    t    l 
1441   11    7 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
145   2   1 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1ie3o1385138141.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2ls0a1385138141.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3tzwu1385138141.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> 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()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4vrh61385138141.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> 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()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5x6291385138141.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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="/var/wessaorg/rcomp/tmp/6tngd1385138141.tab") 
> 
> try(system("convert tmp/1ie3o1385138141.ps tmp/1ie3o1385138141.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ls0a1385138141.ps tmp/2ls0a1385138141.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tzwu1385138141.ps tmp/3tzwu1385138141.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vrh61385138141.ps tmp/4vrh61385138141.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.863   0.468   3.314