R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(26.81,28.24,27.58,27.98,26.81,28.24,27.58,27.98,27.84,27.49,26.97,27.71,27.46,27.04,28.00,27.32,26.36,26.15,25.94,24.00,24.32,23.10,22.92,23.56,22.17,22.36,19.86,20.07,19.21,19.99,20.47,21.17,21.25,21.18,21.21,21.11,21.94,22.56,23.23,19.50,19.32,19.00,18.98,19.88,19.48,19.52,19.52,19.75,19.64,20.23,20.40,20.91,21.95,21.83,22.27,21.99,21.66,20.32,20.62,20.28,20.79,22.86,22.59,23.29,21.87,21.52,22.00,27.84,27.49,26.97,27.71,27.46,27.04,28.00,27.32,26.36,26.15,25.94,24.00,24.32,23.10,22.92,23.56,22.17,22.36,19.86,20.07,19.21,19.99,20.47,21.17,21.25,21.18,21.21,21.11,21.94,22.56,23.23,19.50,19.32,19.00,18.98,19.88,19.48,19.52,19.52,19.75,19.64,20.23,20.40,20.91,21.95,21.83,22.27,21.99,21.66,20.32,20.62,20.28,20.79,22.86,22.59,23.29,21.87,21.52,22.00)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '4'
> main = 'Seasonal Decomposition by Loess'
> par8 <- 'FALSE'
> par7 <- '1'
> par6 <- ''
> par5 <- '1'
> par4 <- ''
> par3 <- '0'
> par2 <- 'periodic'
> par1 <- '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1) #seasonal period
> if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
> par3 <- as.numeric(par3) #s.degree
> if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
> par5 <- as.numeric(par5)#t.degree
> if (par6 != '') par6 <- as.numeric(par6)#l.window
> par7 <- as.numeric(par7)#l.degree
> if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
> nx <- length(x)
> x <- ts(x,frequency=par1)
> if (par6 != '') {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
+ } else {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
+ }
> m$time.series
         seasonal    trend     remainder
 1 Q1 -0.06824041 27.41368 -0.5354367632
 1 Q2  0.06269398 27.51733  0.6599763811
 1 Q3 -0.03626698 27.60617  0.0100985302
 1 Q4  0.04181327 27.63175  0.3064410122
 2 Q1 -0.06824041 27.63074 -0.7525017907
 2 Q2  0.06269398 27.65255  0.5247533631
 2 Q3 -0.03626698 27.79802 -0.1817480658
 2 Q4  0.04181327 27.82078  0.1174043589
 3 Q1 -0.06824041 27.67315  0.2350857909
 3 Q2  0.06269398 27.51788 -0.0905732962
 3 Q3 -0.03626698 27.42639 -0.4201261395
 3 Q4  0.04181327 27.36937  0.2988134806
 4 Q1 -0.06824041 27.42147  0.1067666968
 4 Q2  0.06269398 27.48929 -0.5119838628
 4 Q3 -0.03626698 27.35868  0.6775830477
 4 Q4  0.04181327 27.10538  0.1728099435
 5 Q1 -0.06824041 26.67441 -0.2461711594
 5 Q2  0.06269398 26.05237  0.0349324125
 5 Q3 -0.03626698 25.37366  0.6026048250
 5 Q4  0.04181327 24.70674 -0.7485551386
 6 Q1 -0.06824041 23.94723  0.4410057861
 6 Q2  0.06269398 23.50314 -0.4658348562
 6 Q3 -0.03626698 23.19255 -0.2362782595
 6 Q4  0.04181327 22.87569  0.6424960119
 7 Q1 -0.06824041 22.41906 -0.1808211048
 7 Q2  0.06269398 21.56169  0.7356155753
 7 Q3 -0.03626698 20.71817 -0.8219015305
 7 Q4  0.04181327 20.01903  0.0091569826
 8 Q1 -0.06824041 19.82163 -0.5433915081
 8 Q2  0.06269398 20.03958 -0.1122727531
 8 Q3 -0.03626698 20.47565  0.0306140109
 8 Q4  0.04181327 20.89622  0.2319658972
 9 Q1 -0.06824041 21.12955  0.1886860253
 9 Q2  0.06269398 21.19806 -0.0807546368
 9 Q3 -0.03626698 21.25099 -0.0047185361
 9 Q4  0.04181327 21.50276 -0.4345769306
10 Q1 -0.06824041 21.94225  0.0659946937
10 Q2  0.06269398 22.12200  0.3753037622
10 Q3 -0.03626698 21.57890  1.6873700363
10 Q4  0.04181327 20.66855 -1.2103632635
11 Q1 -0.06824041 19.64136 -0.2531147377
11 Q2  0.06269398 19.21542 -0.2781105096
11 Q3 -0.03626698 19.29719 -0.2809272242
11 Q4  0.04181327 19.42487  0.4133118422
12 Q1 -0.06824041 19.54684  0.0013991587
12 Q2  0.06269398 19.56920 -0.1118967563
12 Q3 -0.03626698 19.58425 -0.0279801919
12 Q4  0.04181327 19.69009  0.0181012683
13 Q1 -0.06824041 19.88356 -0.1753204429
13 Q2  0.06269398 20.14276  0.0245508306
13 Q3 -0.03626698 20.56349 -0.1272209559
13 Q4  0.04181327 21.07214 -0.2039536451
14 Q1 -0.06824041 21.52958  0.4886576637
14 Q2  0.06269398 21.89796 -0.1306551935
14 Q3 -0.03626698 21.98963  0.3166405514
14 Q4  0.04181327 21.79633  0.1518617025
15 Q1 -0.06824041 21.35808  0.3701566666
15 Q2  0.06269398 20.90399 -0.6466805837
15 Q3 -0.03626698 20.57425  0.0820141733
15 Q4  0.04181327 20.76231 -0.5241254969
16 Q1 -0.06824041 21.35311 -0.4948654164
16 Q2  0.06269398 22.04537  0.7519380242
16 Q3 -0.03626698 22.58383  0.0424346933
16 Q4  0.04181327 22.52859  0.7195997890
17 Q1 -0.06824041 22.22943 -0.2911943714
17 Q2  0.06269398 22.54266 -1.0853568947
17 Q3 -0.03626698 23.90779 -1.8715232968
17 Q4  0.04181327 25.53583  2.2623583776
18 Q1 -0.06824041 26.91919  0.6390540662
18 Q2  0.06269398 27.42955 -0.5222394319
18 Q3 -0.03626698 27.36440  0.3818623742
18 Q4  0.04181327 27.42366 -0.0054735259
19 Q1 -0.06824041 27.48892 -0.3806792621
19 Q2  0.06269398 27.36184  0.5754698066
19 Q3 -0.03626698 27.10041  0.2558588135
19 Q4  0.04181327 26.67660 -0.3584114057
20 Q1 -0.06824041 26.05200  0.1662370092
20 Q2  0.06269398 25.37681  0.5004916353
20 Q3 -0.03626698 24.70177 -0.6655062922
20 Q4  0.04181327 23.94942  0.3287655161
21 Q1 -0.06824041 23.50277 -0.3345302636
21 Q2  0.06269398 23.19570 -0.3383913978
21 Q3 -0.03626698 22.87072  0.7255448347
21 Q4  0.04181327 22.42125 -0.2930613985
22 Q1 -0.06824041 21.56132  0.8669201637
22 Q2  0.06269398 20.72132 -0.9240146174
22 Q3 -0.03626698 20.01406  0.0922057818
22 Q4  0.04181327 19.82382 -0.6556318254
23 Q1 -0.06824041 20.03921  0.0190318312
23 Q2  0.06269398 20.47881 -0.0714990247
23 Q3 -0.03626698 20.89125  0.3150146728
23 Q4  0.04181327 21.13174  0.0764456843
24 Q1 -0.06824041 21.19769  0.0505499434
24 Q2  0.06269398 21.25414 -0.1068315204
24 Q3 -0.03626698 21.49780 -0.3515281787
24 Q4  0.04181327 21.94443 -0.0462456710
25 Q1 -0.06824041 22.12163  0.5066083383
25 Q2  0.06269398 21.58205  1.5852571034
25 Q3 -0.03626698 20.66358 -1.1273145351
25 Q4  0.04181327 19.64354 -0.3653551261
26 Q1 -0.06824041 19.21505 -0.1468059375
26 Q2  0.06269398 19.30035 -0.3830401056
26 Q3 -0.03626698 19.41991  0.4963605470
26 Q4  0.04181327 19.54903 -0.1108412533
27 Q1 -0.06824041 19.56883  0.0194078116
27 Q2  0.06269398 19.58740 -0.1300930220
27 Q3 -0.03626698 19.68512  0.1011499494
27 Q4  0.04181327 19.88575 -0.2875608787
28 Q1 -0.06824041 20.14239  0.1558553944
28 Q2  0.06269398 20.56664 -0.2293337346
28 Q3 -0.03626698 21.06717 -0.1209049875
28 Q4  0.04181327 21.53177  0.3764172043
29 Q1 -0.06824041 21.89759  0.0006493662
29 Q2  0.06269398 21.99278  0.2145278240
29 Q3 -0.03626698 21.79136  0.2349103364
29 Q4  0.04181327 21.36027  0.2579161836
30 Q1 -0.06824041 20.90362 -0.5153760281
30 Q2  0.06269398 20.57740 -0.0200985027
30 Q3 -0.03626698 20.75734 -0.4410768865
30 Q4  0.04181327 21.35529 -0.6071059230
31 Q1 -0.06824041 22.04500  0.8832425765
31 Q2  0.06269398 22.58698 -0.0596779284
31 Q3 -0.03626698 22.52362  0.8026483826
31 Q4  0.04181327 22.22684 -0.3986540450
32 Q1 -0.06824041 21.93736 -0.3491235240
32 Q2  0.06269398 21.63426  0.3030456138
> m$win
   s    t    l 
1261    7    5 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
127   1   1 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1yffw1356016623.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/2gekd1356016623.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3x0f61356016623.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/4oqyy1356016623.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5gou01356016623.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/6fot21356016623.tab") 
> 
> try(system("convert tmp/1yffw1356016623.ps tmp/1yffw1356016623.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gekd1356016623.ps tmp/2gekd1356016623.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x0f61356016623.ps tmp/3x0f61356016623.png",intern=TRUE))
character(0)
> try(system("convert tmp/4oqyy1356016623.ps tmp/4oqyy1356016623.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.055   0.543   3.581