Raport_ts_SB
Kravchenko V.
22 10 2020
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library(prophet)
library(lubridate)
library(ggplot2)
library(astsa, quietly=TRUE, warn.conflicts=FALSE)
library(knitr)
library(printr)
library(plyr)
library(dplyr)
library(lubridate)
library(gridExtra)
library(reshape2)
library(TTR)
data <- read.table("SbTs.txt",h=TRUE,dec = ",")
str(data)## 'data.frame': 96 obs. of 2 variables:
## $ Period: Factor w/ 96 levels "2004-01-01","2004-02-01",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ SalesC: int 269607 542391 416533 124751 172263 264779 306335 428759 722836 1172508 ...fix(data)
AP <-data.frame(data$Period)
data.time <- ymd(AP$data.Period)
str(data.time)## Date[1:96], format: "2004-01-01" "2004-02-01" "2004-03-01" "2004-04-01" "2004-05-01" ...dates.saleC <- data$SalesC
dates.saleC ## [1] 269607 542391 416533 124751 172263 264779 306335 428759 722836
## [10] 1172508 1006760 1236768 554051 514427 534686 792693 386033 470864
## [19] 594361 698516 1087468 1587424 1574411 1791686 863407 924142 876372
## [28] 792964 491401 672489 633884 1097905 1994863 2226363 2197191 2376759
## [37] 1372341 1577593 1628783 1128700 869352 1622662 1489598 1752315 2861010
## [46] 2609937 3867529 3241078 1678588 2006365 2154445 1548438 1003634 1757179
## [55] 1849788 2004677 3248930 3482077 2885166 3161956 1168752 1316905 1250966
## [64] 1256732 1585652 1127210 1544773 1671149 1807886 2648822 2341570 3258579
## [73] 2345324 2244962 2311521 1903100 1585968 2520926 2454979 2407938 3453892
## [82] 4557630 3517299 5324057 2787904 3315663 2622287 3372816 2104893 3033372
## [91] 3130840 3022317 4265530 5536780 4202056 6253253time.serias <- data.frame(data.time,dates.saleC)
time.serias| data.time | dates.saleC |
|---|---|
| 2004-01-01 | 269607 |
| 2004-02-01 | 542391 |
| 2004-03-01 | 416533 |
| 2004-04-01 | 124751 |
| 2004-05-01 | 172263 |
| 2004-06-01 | 264779 |
| 2004-07-01 | 306335 |
| 2004-08-01 | 428759 |
| 2004-09-01 | 722836 |
| 2004-10-01 | 1172508 |
| 2004-11-01 | 1006760 |
| 2004-12-01 | 1236768 |
| 2005-01-01 | 554051 |
| 2005-02-01 | 514427 |
| 2005-03-01 | 534686 |
| 2005-04-01 | 792693 |
| 2005-05-01 | 386033 |
| 2005-06-01 | 470864 |
| 2005-07-01 | 594361 |
| 2005-08-01 | 698516 |
| 2005-09-01 | 1087468 |
| 2005-10-01 | 1587424 |
| 2005-11-01 | 1574411 |
| 2005-12-01 | 1791686 |
| 2006-01-01 | 863407 |
| 2006-02-01 | 924142 |
| 2006-03-01 | 876372 |
| 2006-04-01 | 792964 |
| 2006-05-01 | 491401 |
| 2006-06-01 | 672489 |
| 2006-07-01 | 633884 |
| 2006-08-01 | 1097905 |
| 2006-09-01 | 1994863 |
| 2006-10-01 | 2226363 |
| 2006-11-01 | 2197191 |
| 2006-12-01 | 2376759 |
| 2007-01-01 | 1372341 |
| 2007-02-01 | 1577593 |
| 2007-03-01 | 1628783 |
| 2007-04-01 | 1128700 |
| 2007-05-01 | 869352 |
| 2007-06-01 | 1622662 |
| 2007-07-01 | 1489598 |
| 2007-08-01 | 1752315 |
| 2007-09-01 | 2861010 |
| 2007-10-01 | 2609937 |
| 2007-11-01 | 3867529 |
| 2007-12-01 | 3241078 |
| 2008-01-01 | 1678588 |
| 2008-02-01 | 2006365 |
| 2008-03-01 | 2154445 |
| 2008-04-01 | 1548438 |
| 2008-05-01 | 1003634 |
| 2008-06-01 | 1757179 |
| 2008-07-01 | 1849788 |
| 2008-08-01 | 2004677 |
| 2008-09-01 | 3248930 |
| 2008-10-01 | 3482077 |
| 2008-11-01 | 2885166 |
| 2008-12-01 | 3161956 |
| 2009-01-01 | 1168752 |
| 2009-02-01 | 1316905 |
| 2009-03-01 | 1250966 |
| 2009-04-01 | 1256732 |
| 2009-05-01 | 1585652 |
| 2009-06-01 | 1127210 |
| 2009-07-01 | 1544773 |
| 2009-08-01 | 1671149 |
| 2009-09-01 | 1807886 |
| 2009-10-01 | 2648822 |
| 2009-11-01 | 2341570 |
| 2009-12-01 | 3258579 |
| 2010-01-01 | 2345324 |
| 2010-02-01 | 2244962 |
| 2010-03-01 | 2311521 |
| 2010-04-01 | 1903100 |
| 2010-05-01 | 1585968 |
| 2010-06-01 | 2520926 |
| 2010-07-01 | 2454979 |
| 2010-08-01 | 2407938 |
| 2010-09-01 | 3453892 |
| 2010-10-01 | 4557630 |
| 2010-11-01 | 3517299 |
| 2010-12-01 | 5324057 |
| 2011-01-01 | 2787904 |
| 2011-02-01 | 3315663 |
| 2011-03-01 | 2622287 |
| 2011-04-01 | 3372816 |
| 2011-05-01 | 2104893 |
| 2011-06-01 | 3033372 |
| 2011-07-01 | 3130840 |
| 2011-08-01 | 3022317 |
| 2011-09-01 | 4265530 |
| 2011-10-01 | 5536780 |
| 2011-11-01 | 4202056 |
| 2011-12-01 | 6253253 |
ts(time.serias,frequency = 12,start = c(2004,1))| data.time | dates.saleC |
|---|---|
| 12418 | 269607 |
| 12449 | 542391 |
| 12478 | 416533 |
| 12509 | 124751 |
| 12539 | 172263 |
| 12570 | 264779 |
| 12600 | 306335 |
| 12631 | 428759 |
| 12662 | 722836 |
| 12692 | 1172508 |
| 12723 | 1006760 |
| 12753 | 1236768 |
| 12784 | 554051 |
| 12815 | 514427 |
| 12843 | 534686 |
| 12874 | 792693 |
| 12904 | 386033 |
| 12935 | 470864 |
| 12965 | 594361 |
| 12996 | 698516 |
| 13027 | 1087468 |
| 13057 | 1587424 |
| 13088 | 1574411 |
| 13118 | 1791686 |
| 13149 | 863407 |
| 13180 | 924142 |
| 13208 | 876372 |
| 13239 | 792964 |
| 13269 | 491401 |
| 13300 | 672489 |
| 13330 | 633884 |
| 13361 | 1097905 |
| 13392 | 1994863 |
| 13422 | 2226363 |
| 13453 | 2197191 |
| 13483 | 2376759 |
| 13514 | 1372341 |
| 13545 | 1577593 |
| 13573 | 1628783 |
| 13604 | 1128700 |
| 13634 | 869352 |
| 13665 | 1622662 |
| 13695 | 1489598 |
| 13726 | 1752315 |
| 13757 | 2861010 |
| 13787 | 2609937 |
| 13818 | 3867529 |
| 13848 | 3241078 |
| 13879 | 1678588 |
| 13910 | 2006365 |
| 13939 | 2154445 |
| 13970 | 1548438 |
| 14000 | 1003634 |
| 14031 | 1757179 |
| 14061 | 1849788 |
| 14092 | 2004677 |
| 14123 | 3248930 |
| 14153 | 3482077 |
| 14184 | 2885166 |
| 14214 | 3161956 |
| 14245 | 1168752 |
| 14276 | 1316905 |
| 14304 | 1250966 |
| 14335 | 1256732 |
| 14365 | 1585652 |
| 14396 | 1127210 |
| 14426 | 1544773 |
| 14457 | 1671149 |
| 14488 | 1807886 |
| 14518 | 2648822 |
| 14549 | 2341570 |
| 14579 | 3258579 |
| 14610 | 2345324 |
| 14641 | 2244962 |
| 14669 | 2311521 |
| 14700 | 1903100 |
| 14730 | 1585968 |
| 14761 | 2520926 |
| 14791 | 2454979 |
| 14822 | 2407938 |
| 14853 | 3453892 |
| 14883 | 4557630 |
| 14914 | 3517299 |
| 14944 | 5324057 |
| 14975 | 2787904 |
| 15006 | 3315663 |
| 15034 | 2622287 |
| 15065 | 3372816 |
| 15095 | 2104893 |
| 15126 | 3033372 |
| 15156 | 3130840 |
| 15187 | 3022317 |
| 15218 | 4265530 |
| 15248 | 5536780 |
| 15279 | 4202056 |
| 15309 | 6253253 |
z <- ts(matrix(rnorm(300),100,2),
start = c(2004,1),
frequency = 12)
class(z)## [1] "mts" "ts" "matrix"plot(z,plot.type = "single",
lty=1:3)
plot(time.serias)
time.serias <- ts(time.serias, start = c(2004, 1), end = c(2019, 1), frequency = 12)
decompose(time.serias, type = c("additive", "multiplicative"), filter = NULL)## $x
## data.time dates.saleC
## Jan 2004 12418 269607
## Feb 2004 12449 542391
## Mar 2004 12478 416533
## Apr 2004 12509 124751
## May 2004 12539 172263
## Jun 2004 12570 264779
## Jul 2004 12600 306335
## Aug 2004 12631 428759
## Sep 2004 12662 722836
## Oct 2004 12692 1172508
## Nov 2004 12723 1006760
## Dec 2004 12753 1236768
## Jan 2005 12784 554051
## Feb 2005 12815 514427
## Mar 2005 12843 534686
## Apr 2005 12874 792693
## May 2005 12904 386033
## Jun 2005 12935 470864
## Jul 2005 12965 594361
## Aug 2005 12996 698516
## Sep 2005 13027 1087468
## Oct 2005 13057 1587424
## Nov 2005 13088 1574411
## Dec 2005 13118 1791686
## Jan 2006 13149 863407
## Feb 2006 13180 924142
## Mar 2006 13208 876372
## Apr 2006 13239 792964
## May 2006 13269 491401
## Jun 2006 13300 672489
## Jul 2006 13330 633884
## Aug 2006 13361 1097905
## Sep 2006 13392 1994863
## Oct 2006 13422 2226363
## Nov 2006 13453 2197191
## Dec 2006 13483 2376759
## Jan 2007 13514 1372341
## Feb 2007 13545 1577593
## Mar 2007 13573 1628783
## Apr 2007 13604 1128700
## May 2007 13634 869352
## Jun 2007 13665 1622662
## Jul 2007 13695 1489598
## Aug 2007 13726 1752315
## Sep 2007 13757 2861010
## Oct 2007 13787 2609937
## Nov 2007 13818 3867529
## Dec 2007 13848 3241078
## Jan 2008 13879 1678588
## Feb 2008 13910 2006365
## Mar 2008 13939 2154445
## Apr 2008 13970 1548438
## May 2008 14000 1003634
## Jun 2008 14031 1757179
## Jul 2008 14061 1849788
## Aug 2008 14092 2004677
## Sep 2008 14123 3248930
## Oct 2008 14153 3482077
## Nov 2008 14184 2885166
## Dec 2008 14214 3161956
## Jan 2009 14245 1168752
## Feb 2009 14276 1316905
## Mar 2009 14304 1250966
## Apr 2009 14335 1256732
## May 2009 14365 1585652
## Jun 2009 14396 1127210
## Jul 2009 14426 1544773
## Aug 2009 14457 1671149
## Sep 2009 14488 1807886
## Oct 2009 14518 2648822
## Nov 2009 14549 2341570
## Dec 2009 14579 3258579
## Jan 2010 14610 2345324
## Feb 2010 14641 2244962
## Mar 2010 14669 2311521
## Apr 2010 14700 1903100
## May 2010 14730 1585968
## Jun 2010 14761 2520926
## Jul 2010 14791 2454979
## Aug 2010 14822 2407938
## Sep 2010 14853 3453892
## Oct 2010 14883 4557630
## Nov 2010 14914 3517299
## Dec 2010 14944 5324057
## Jan 2011 14975 2787904
## Feb 2011 15006 3315663
## Mar 2011 15034 2622287
## Apr 2011 15065 3372816
## May 2011 15095 2104893
## Jun 2011 15126 3033372
## Jul 2011 15156 3130840
## Aug 2011 15187 3022317
## Sep 2011 15218 4265530
## Oct 2011 15248 5536780
## Nov 2011 15279 4202056
## Dec 2011 15309 6253253
## Jan 2012 12418 269607
## Feb 2012 12449 542391
## Mar 2012 12478 416533
## Apr 2012 12509 124751
## May 2012 12539 172263
## Jun 2012 12570 264779
## Jul 2012 12600 306335
## Aug 2012 12631 428759
## Sep 2012 12662 722836
## Oct 2012 12692 1172508
## Nov 2012 12723 1006760
## Dec 2012 12753 1236768
## Jan 2013 12784 554051
## Feb 2013 12815 514427
## Mar 2013 12843 534686
## Apr 2013 12874 792693
## May 2013 12904 386033
## Jun 2013 12935 470864
## Jul 2013 12965 594361
## Aug 2013 12996 698516
## Sep 2013 13027 1087468
## Oct 2013 13057 1587424
## Nov 2013 13088 1574411
## Dec 2013 13118 1791686
## Jan 2014 13149 863407
## Feb 2014 13180 924142
## Mar 2014 13208 876372
## Apr 2014 13239 792964
## May 2014 13269 491401
## Jun 2014 13300 672489
## Jul 2014 13330 633884
## Aug 2014 13361 1097905
## Sep 2014 13392 1994863
## Oct 2014 13422 2226363
## Nov 2014 13453 2197191
## Dec 2014 13483 2376759
## Jan 2015 13514 1372341
## Feb 2015 13545 1577593
## Mar 2015 13573 1628783
## Apr 2015 13604 1128700
## May 2015 13634 869352
## Jun 2015 13665 1622662
## Jul 2015 13695 1489598
## Aug 2015 13726 1752315
## Sep 2015 13757 2861010
## Oct 2015 13787 2609937
## Nov 2015 13818 3867529
## Dec 2015 13848 3241078
## Jan 2016 13879 1678588
## Feb 2016 13910 2006365
## Mar 2016 13939 2154445
## Apr 2016 13970 1548438
## May 2016 14000 1003634
## Jun 2016 14031 1757179
## Jul 2016 14061 1849788
## Aug 2016 14092 2004677
## Sep 2016 14123 3248930
## Oct 2016 14153 3482077
## Nov 2016 14184 2885166
## Dec 2016 14214 3161956
## Jan 2017 14245 1168752
## Feb 2017 14276 1316905
## Mar 2017 14304 1250966
## Apr 2017 14335 1256732
## May 2017 14365 1585652
## Jun 2017 14396 1127210
## Jul 2017 14426 1544773
## Aug 2017 14457 1671149
## Sep 2017 14488 1807886
## Oct 2017 14518 2648822
## Nov 2017 14549 2341570
## Dec 2017 14579 3258579
## Jan 2018 14610 2345324
## Feb 2018 14641 2244962
## Mar 2018 14669 2311521
## Apr 2018 14700 1903100
## May 2018 14730 1585968
## Jun 2018 14761 2520926
## Jul 2018 14791 2454979
## Aug 2018 14822 2407938
## Sep 2018 14853 3453892
## Oct 2018 14883 4557630
## Nov 2018 14914 3517299
## Dec 2018 14944 5324057
## Jan 2019 14975 2787904
##
## $seasonal
## Jan Feb Mar Apr May Jun Jul
## 2004 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2005 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2006 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2007 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2008 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2009 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2010 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2011 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2012 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2013 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2014 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2015 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2016 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2017 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2018 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2019 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2020 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2021 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2022 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2023 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2024 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2025 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2026 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2027 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2028 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2029 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2030 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2031 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2032 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2033 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## 2034 609656.6 -207193.7
## Aug Sep Oct Nov Dec
## 2004 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2005 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2006 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2007 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2008 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2009 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2010 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2011 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2012 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2013 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2014 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2015 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2016 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2017 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2018 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2019 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2020 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2021 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2022 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2023 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2024 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2025 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2026 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2027 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2028 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2029 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2030 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2031 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2032 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2033 -203984.1 -118316.8 248785.0 471301.4 392129.0
## 2034
##
## $trend
## [,1] [,2]
## Jan 2004 NA NA
## Feb 2004 NA NA
## Mar 2004 NA NA
## Apr 2004 NA NA
## May 2004 NA NA
## Jun 2004 NA NA
## Jul 2004 12600.58 567209.3
## Aug 2004 12631.08 577896.0
## Sep 2004 12661.54 581653.9
## Oct 2004 12691.96 614407.8
## Nov 2004 12722.38 651145.8
## Dec 2004 12752.79 668639.8
## Jan 2005 12783.21 689227.8
## Feb 2005 12813.62 712468.7
## Mar 2005 12844.04 738901.6
## Apr 2005 12874.46 771382.8
## May 2005 12904.87 812323.0
## Jun 2005 12935.29 859096.7
## Jul 2005 12965.71 895108.2
## Aug 2005 12996.12 925069.5
## Sep 2005 13026.54 956377.8
## Oct 2005 13056.96 970626.0
## Nov 2005 13087.37 975027.7
## Dec 2005 13117.79 987819.0
## Jan 2006 13148.21 997866.9
## Feb 2006 13178.62 1016154.9
## Mar 2006 13209.04 1070604.2
## Apr 2006 13239.46 1135034.8
## May 2006 13269.88 1187606.4
## Jun 2006 13300.29 1237933.6
## Jul 2006 13330.71 1283517.2
## Aug 2006 13361.12 1331950.0
## Sep 2006 13391.54 1390527.5
## Oct 2006 13421.96 1435867.0
## Nov 2006 13452.38 1465604.0
## Dec 2006 13482.79 1520942.5
## Jan 2007 13513.21 1596187.7
## Feb 2007 13543.63 1659109.6
## Mar 2007 13574.04 1722466.1
## Apr 2007 13604.46 1774537.8
## May 2007 13634.87 1860117.5
## Jun 2007 13665.29 1965728.2
## Jul 2007 13695.71 2014501.8
## Aug 2007 13726.12 2045127.6
## Sep 2007 13756.58 2084895.7
## Oct 2007 13787.08 2124287.3
## Nov 2007 13817.58 2147371.5
## Dec 2007 13848.08 2158571.5
## Jan 2008 13878.58 2179184.2
## Feb 2008 13909.08 2204707.2
## Mar 2008 13939.58 2231385.7
## Apr 2008 13970.08 2283888.2
## May 2008 14000.58 2279295.5
## Jun 2008 14031.08 2235067.0
## Jul 2008 14061.58 2210527.1
## Aug 2008 14092.08 2160556.4
## Sep 2008 14122.54 2094184.0
## Oct 2008 14152.96 2044384.6
## Nov 2008 14183.38 2056480.9
## Dec 2008 14213.79 2054483.0
## Jan 2009 14244.21 2015525.3
## Feb 2009 14274.62 1988919.3
## Mar 2009 14305.04 1914978.8
## Apr 2009 14335.46 1820216.4
## May 2009 14365.87 1762847.6
## Jun 2009 14396.29 1744223.7
## Jul 2009 14426.71 1797273.5
## Aug 2009 14457.12 1884966.4
## Sep 2009 14487.54 1967825.2
## Oct 2009 14517.96 2038947.0
## Nov 2009 14548.37 2065892.2
## Dec 2009 14578.79 2123976.8
## Jan 2010 14609.21 2219973.6
## Feb 2010 14639.62 2288598.4
## Mar 2010 14670.04 2387881.5
## Apr 2010 14700.46 2535998.8
## May 2010 14730.88 2664521.1
## Jun 2010 14761.29 2799571.4
## Jul 2010 14791.71 2904073.8
## Aug 2010 14822.12 2967127.2
## Sep 2010 14852.54 3024688.3
## Oct 2010 14882.96 3098875.1
## Nov 2010 14913.38 3181735.1
## Dec 2010 14943.79 3224708.9
## Jan 2011 14974.21 3274221.7
## Feb 2011 15004.63 3327981.7
## Mar 2011 15035.04 3387399.1
## Apr 2011 15065.46 3462015.2
## May 2011 15095.87 3531344.7
## Jun 2011 15126.29 3598592.8
## Jul 2011 15034.96 3532380.2
## Aug 2011 14821.87 3311898.2
## Sep 2011 14608.83 3104438.8
## Oct 2011 14395.83 2877196.3
## Nov 2011 14182.83 2661334.0
## Dec 2011 13969.83 2465449.7
## Jan 2012 13756.83 2232404.0
## Feb 2012 13543.83 2006651.3
## Mar 2012 13330.83 1750974.2
## Apr 2012 13117.83 1421517.2
## May 2012 12904.83 1106535.2
## Jun 2012 12691.83 764377.7
## Jul 2012 12600.58 567209.3
## Aug 2012 12631.08 577896.0
## Sep 2012 12661.54 581653.9
## Oct 2012 12691.96 614407.8
## Nov 2012 12722.38 651145.8
## Dec 2012 12752.79 668639.8
## Jan 2013 12783.21 689227.8
## Feb 2013 12813.62 712468.7
## Mar 2013 12844.04 738901.6
## Apr 2013 12874.46 771382.8
## May 2013 12904.87 812323.0
## Jun 2013 12935.29 859096.7
## Jul 2013 12965.71 895108.2
## Aug 2013 12996.12 925069.5
## Sep 2013 13026.54 956377.8
## Oct 2013 13056.96 970626.0
## Nov 2013 13087.37 975027.7
## Dec 2013 13117.79 987819.0
## Jan 2014 13148.21 997866.9
## Feb 2014 13178.62 1016154.9
## Mar 2014 13209.04 1070604.2
## Apr 2014 13239.46 1135034.8
## May 2014 13269.88 1187606.4
## Jun 2014 13300.29 1237933.6
## Jul 2014 13330.71 1283517.2
## Aug 2014 13361.12 1331950.0
## Sep 2014 13391.54 1390527.5
## Oct 2014 13421.96 1435867.0
## Nov 2014 13452.38 1465604.0
## Dec 2014 13482.79 1520942.5
## Jan 2015 13513.21 1596187.7
## Feb 2015 13543.63 1659109.6
## Mar 2015 13574.04 1722466.1
## Apr 2015 13604.46 1774537.8
## May 2015 13634.87 1860117.5
## Jun 2015 13665.29 1965728.2
## Jul 2015 13695.71 2014501.8
## Aug 2015 13726.12 2045127.6
## Sep 2015 13756.58 2084895.7
## Oct 2015 13787.08 2124287.3
## Nov 2015 13817.58 2147371.5
## Dec 2015 13848.08 2158571.5
## Jan 2016 13878.58 2179184.2
## Feb 2016 13909.08 2204707.2
## Mar 2016 13939.58 2231385.7
## Apr 2016 13970.08 2283888.2
## May 2016 14000.58 2279295.5
## Jun 2016 14031.08 2235067.0
## Jul 2016 14061.58 2210527.1
## Aug 2016 14092.08 2160556.4
## Sep 2016 14122.54 2094184.0
## Oct 2016 14152.96 2044384.6
## Nov 2016 14183.38 2056480.9
## Dec 2016 14213.79 2054483.0
## Jan 2017 14244.21 2015525.3
## Feb 2017 14274.62 1988919.3
## Mar 2017 14305.04 1914978.8
## Apr 2017 14335.46 1820216.4
## May 2017 14365.87 1762847.6
## Jun 2017 14396.29 1744223.7
## Jul 2017 14426.71 1797273.5
## Aug 2017 14457.12 1884966.4
## Sep 2017 14487.54 1967825.2
## Oct 2017 14517.96 2038947.0
## Nov 2017 14548.37 2065892.2
## Dec 2017 14578.79 2123976.8
## Jan 2018 14609.21 2219973.6
## Feb 2018 14639.62 2288598.4
## Mar 2018 14670.04 2387881.5
## Apr 2018 14700.46 2535998.8
## May 2018 14730.88 2664521.1
## Jun 2018 14761.29 2799571.4
## Jul 2018 14791.71 2904073.8
## Aug 2018 NA NA
## Sep 2018 NA NA
## Oct 2018 NA NA
## Nov 2018 NA NA
## Dec 2018 NA NA
## Jan 2019 NA NA
##
## $random
## x - seasonal.x.data.time x - seasonal.x.dates.saleC
## Jan 2004 NA NA
## Feb 2004 NA NA
## Mar 2004 NA NA
## Apr 2004 NA NA
## May 2004 NA NA
## Jun 2004 NA NA
## Jul 2004 218022.4 -42851.396
## Aug 2004 203984.0 54847.082
## Sep 2004 118317.2 259498.909
## Oct 2004 -248785.0 309315.160
## Nov 2004 -471300.8 -115687.258
## Dec 2004 -392128.8 175999.206
## Jan 2005 -609655.8 -744833.320
## Feb 2005 207195.0 9151.955
## Mar 2005 141741.7 -62472.805
## Apr 2005 165688.2 186998.898
## May 2005 253693.1 -172596.096
## Jun 2005 413228.9 24996.415
## Jul 2005 218022.2 -82724.230
## Aug 2005 203984.0 -22569.376
## Sep 2005 118317.2 249406.950
## Oct 2005 -248785.0 368012.952
## Nov 2005 -471300.8 128081.909
## Dec 2005 -392128.8 411737.956
## Jan 2006 -609655.8 -744116.445
## Feb 2006 207195.0 115180.788
## Mar 2006 141741.7 -52489.430
## Apr 2006 165688.2 -176382.143
## May 2006 253693.1 -442511.471
## Jun 2006 413228.9 -152215.460
## Jul 2006 218022.2 -431610.313
## Aug 2006 203984.0 -30060.876
## Sep 2006 118317.2 722652.242
## Oct 2006 -248785.0 541710.994
## Nov 2006 -471300.8 260285.617
## Dec 2006 -392128.8 463687.540
## Jan 2007 -609655.8 -833503.320
## Feb 2007 207195.0 125677.080
## Mar 2007 141741.7 48059.653
## Apr 2007 165688.2 -480149.185
## May 2007 253693.1 -737071.554
## Jun 2007 413228.9 70162.956
## Jul 2007 218022.2 -306880.855
## Aug 2007 203984.0 -88828.501
## Sep 2007 118317.2 894431.117
## Oct 2007 -248785.1 236864.660
## Nov 2007 -471301.0 1248856.075
## Dec 2007 -392129.1 690377.540
## Jan 2008 -609656.2 -1110252.820
## Feb 2008 207194.6 8851.413
## Mar 2008 141742.2 64802.111
## Apr 2008 165688.6 -569761.518
## May 2008 253693.4 -1021967.596
## Jun 2008 413229.1 -64658.835
## Jul 2008 218022.4 -142716.146
## Aug 2008 203984.0 48104.665
## Sep 2008 118317.2 1273062.825
## Oct 2008 -248785.0 1188907.410
## Nov 2008 -471300.8 357383.659
## Dec 2008 -392128.8 715344.040
## Jan 2009 -609655.8 -1456429.862
## Feb 2009 207195.0 -464820.670
## Mar 2009 141741.7 -522270.055
## Apr 2009 165688.2 -397795.727
## May 2009 253693.1 76498.363
## Jun 2009 413228.9 -203784.544
## Jul 2009 218022.2 -34477.563
## Aug 2009 203984.0 -9833.293
## Sep 2009 118317.2 -41622.425
## Oct 2009 -248785.0 361089.994
## Nov 2009 -471300.8 -195623.591
## Dec 2009 -392128.8 742473.165
## Jan 2010 -609655.8 -484306.154
## Feb 2010 207195.0 163557.288
## Mar 2010 141741.7 65382.278
## Apr 2010 165688.2 -467210.102
## May 2010 253693.1 -824859.179
## Jun 2010 413228.9 134583.748
## Jul 2010 218022.2 -231071.896
## Aug 2010 203984.0 -355205.126
## Sep 2010 118317.2 547520.450
## Oct 2010 -248785.0 1209969.910
## Nov 2010 -471300.8 -135737.550
## Dec 2010 -392128.8 1707219.081
## Jan 2011 -609655.8 -1095974.279
## Feb 2011 207195.0 194874.955
## Mar 2011 141741.7 -623369.305
## Apr 2011 165688.2 76489.398
## May 2011 253693.1 -1172757.762
## Jun 2011 413228.9 -151991.585
## Jul 2011 218144.0 -183517.271
## Aug 2011 204349.2 -85597.085
## Sep 2011 118926.0 1279408.034
## Oct 2011 -247932.8 2410798.702
## Nov 2011 -470205.3 1069420.575
## Dec 2011 -390789.8 3395674.290
## Jan 2012 -610995.4 -2572453.529
## Feb 2012 206098.8 -1257066.670
## Mar 2012 140889.9 -1192698.389
## Apr 2012 165079.8 -1131077.602
## May 2012 253328.1 -680578.304
## Jun 2012 413107.3 -86369.544
## Jul 2012 218022.4 -42851.396
## Aug 2012 203984.0 54847.082
## Sep 2012 118317.2 259498.909
## Oct 2012 -248785.0 309315.160
## Nov 2012 -471300.8 -115687.258
## Dec 2012 -392128.8 175999.206
## Jan 2013 -609655.8 -744833.320
## Feb 2013 207195.0 9151.955
## Mar 2013 141741.7 -62472.805
## Apr 2013 165688.2 186998.898
## May 2013 253693.1 -172596.096
## Jun 2013 413228.9 24996.415
## Jul 2013 218022.2 -82724.230
## Aug 2013 203984.0 -22569.376
## Sep 2013 118317.2 249406.950
## Oct 2013 -248785.0 368012.952
## Nov 2013 -471300.8 128081.909
## Dec 2013 -392128.8 411737.956
## Jan 2014 -609655.8 -744116.445
## Feb 2014 207195.0 115180.788
## Mar 2014 141741.7 -52489.430
## Apr 2014 165688.2 -176382.143
## May 2014 253693.1 -442511.471
## Jun 2014 413228.9 -152215.460
## Jul 2014 218022.2 -431610.313
## Aug 2014 203984.0 -30060.876
## Sep 2014 118317.2 722652.242
## Oct 2014 -248785.0 541710.994
## Nov 2014 -471300.8 260285.617
## Dec 2014 -392128.8 463687.540
## Jan 2015 -609655.8 -833503.320
## Feb 2015 207195.0 125677.080
## Mar 2015 141741.7 48059.653
## Apr 2015 165688.2 -480149.185
## May 2015 253693.1 -737071.554
## Jun 2015 413228.9 70162.956
## Jul 2015 218022.2 -306880.855
## Aug 2015 203984.0 -88828.501
## Sep 2015 118317.2 894431.117
## Oct 2015 -248785.1 236864.660
## Nov 2015 -471301.0 1248856.075
## Dec 2015 -392129.1 690377.540
## Jan 2016 -609656.2 -1110252.820
## Feb 2016 207194.6 8851.413
## Mar 2016 141742.2 64802.111
## Apr 2016 165688.6 -569761.518
## May 2016 253693.4 -1021967.596
## Jun 2016 413229.1 -64658.835
## Jul 2016 218022.4 -142716.146
## Aug 2016 203984.0 48104.665
## Sep 2016 118317.2 1273062.825
## Oct 2016 -248785.0 1188907.410
## Nov 2016 -471300.8 357383.659
## Dec 2016 -392128.8 715344.040
## Jan 2017 -609655.8 -1456429.862
## Feb 2017 207195.0 -464820.670
## Mar 2017 141741.7 -522270.055
## Apr 2017 165688.2 -397795.727
## May 2017 253693.1 76498.363
## Jun 2017 413228.9 -203784.544
## Jul 2017 218022.2 -34477.563
## Aug 2017 203984.0 -9833.293
## Sep 2017 118317.2 -41622.425
## Oct 2017 -248785.0 361089.994
## Nov 2017 -471300.8 -195623.591
## Dec 2017 -392128.8 742473.165
## Jan 2018 -609655.8 -484306.154
## Feb 2018 207195.0 163557.288
## Mar 2018 141741.7 65382.278
## Apr 2018 165688.2 -467210.102
## May 2018 253693.1 -824859.179
## Jun 2018 413228.9 134583.748
## Jul 2018 218022.2 -231071.896
## Aug 2018 NA NA
## Sep 2018 NA NA
## Oct 2018 NA NA
## Nov 2018 NA NA
## Dec 2018 NA NA
## Jan 2019 NA NA
##
## $figure
## [1] 609656.6 -207193.7 -141742.8 -165688.6 -253693.9 -413229.2 -218022.9
## [8] -203984.1 -118316.8 248785.0 471301.4 392129.0
##
## $type
## [1] "additive"
##
## attr(,"class")
## [1] "decomposed.ts"plot(decompose(time.serias))
plot(decompose(time.serias,type = "additive"))
DecomposeAP <-decompose(time.serias,type ="additive")
plot(DecomposeAP,xlim=c(2004,2019),ylim=c(0,1700000))
SBrend <-window(DecomposeAP$trend,start = 2004,end = c(2019,1))
plot(SBrend)
#plot(SB.diff)
newSB <- DecomposeAP$trend*DecomposeAP$seasonal*DecomposeAP$random
plot(newSB)
SB.diff <- newSB-time.serias
SB.diff| newSB.DecomposeAP\(trend * DecomposeAP\)seasonal.DecomposeAP$trend.1 | newSB.DecomposeAP\(trend * DecomposeAP\)seasonal.DecomposeAP$trend.2 |
|---|---|
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
| -5.989545e+14 | 5.299203e+15 |
| -5.255729e+14 | -6.465461e+15 |
| -1.772479e+14 | -1.785856e+16 |
| -7.855557e+14 | 4.728051e+16 |
| -2.825954e+15 | -3.550280e+16 |
| -1.960934e+15 | 4.614577e+16 |
| -4.751271e+15 | -3.129732e+17 |
| -5.500825e+14 | -1.351002e+15 |
| -2.580479e+14 | 6.543024e+15 |
| -3.534380e+14 | -2.390021e+16 |
| -8.305629e+14 | 3.556885e+16 |
| -2.208807e+15 | -8.873823e+15 |
| -6.163100e+14 | 1.614397e+16 |
| -5.407620e+14 | 4.258829e+15 |
| -1.823575e+14 | -2.822178e+16 |
| -8.081470e+14 | 8.886674e+16 |
| -2.907030e+15 | 5.885773e+16 |
| -2.017058e+15 | 1.594877e+17 |
| -4.886935e+15 | -4.526878e+17 |
| -5.657518e+14 | -2.425026e+16 |
| -2.653811e+14 | 7.965293e+15 |
| -3.634582e+14 | 3.317085e+16 |
| -8.540544e+14 | 1.333236e+17 |
| -2.271134e+15 | 7.786586e+16 |
| -6.336598e+14 | 1.207802e+17 |
| -5.559495e+14 | 8.167438e+15 |
| -1.874671e+14 | -1.188927e+17 |
| -8.307383e+14 | 1.935112e+17 |
| -2.988105e+15 | 1.797900e+17 |
| -2.073182e+15 | 2.765459e+17 |
| -5.022598e+15 | -8.111040e+17 |
| -5.814210e+14 | -4.320238e+16 |
| -2.727143e+14 | -1.173363e+16 |
| -3.734785e+14 | 1.411738e+17 |
| -8.775460e+14 | 3.478245e+17 |
| -2.333461e+15 | -5.699310e+16 |
| -6.510097e+14 | 1.347844e+17 |
| -5.711369e+14 | 3.705689e+16 |
| -1.925772e+14 | -2.206366e+17 |
| -8.533377e+14 | 1.251808e+17 |
| -3.069228e+15 | 1.263916e+18 |
| -2.129353e+15 | 5.843621e+17 |
| -5.158404e+15 | -1.475031e+18 |
| -5.971087e+14 | -4.043338e+15 |
| -2.800592e+14 | -2.049579e+16 |
| -3.835167e+14 | 2.156059e+17 |
| -9.010841e+14 | 5.909461e+17 |
| -2.395924e+15 | 5.971857e+16 |
| -6.684015e+14 | 6.878142e+16 |
| -5.863644e+14 | -2.120065e+16 |
| -1.977003e+14 | -3.154358e+17 |
| -8.759828e+14 | 6.046929e+17 |
| -3.150478e+15 | 3.463842e+17 |
| -2.185585e+15 | 5.762971e+17 |
| -5.294297e+15 | -1.789629e+18 |
| -6.128025e+14 | 1.915486e+17 |
| -2.874007e+14 | 1.417621e+17 |
| -3.935464e+14 | 1.199709e+17 |
| -9.245934e+14 | -3.421189e+16 |
| -2.458285e+15 | 1.468806e+17 |
| -6.857569e+14 | 1.350992e+16 |
| -6.015535e+14 | 3.780932e+15 |
| -2.028099e+14 | 9.690814e+15 |
| -8.985741e+14 | 1.831663e+17 |
| -3.231554e+15 | -1.904705e+17 |
| -2.241709e+15 | 6.183858e+17 |
| -5.429960e+15 | -6.554704e+17 |
| -6.284718e+14 | -7.755610e+16 |
| -2.947339e+14 | -2.212961e+16 |
| -4.035666e+14 | 1.963152e+17 |
| -9.480850e+14 | 5.575824e+17 |
| -2.520612e+15 | -1.556952e+17 |
| -7.031068e+14 | 1.463043e+17 |
| -6.167409e+14 | 2.149867e+17 |
| -2.079195e+14 | -1.959419e+17 |
| -9.211654e+14 | 9.328307e+17 |
| -3.312630e+15 | -2.035461e+17 |
| -2.297833e+15 | 2.158782e+18 |
| -5.565624e+15 | -2.187730e+18 |
| -6.441410e+14 | -1.343734e+17 |
| -3.020670e+14 | 2.993041e+17 |
| -4.135868e+14 | -4.387559e+16 |
| -9.715765e+14 | 1.050651e+18 |
| -2.582939e+15 | 2.260181e+17 |
| -7.150685e+14 | 1.413340e+17 |
| -6.178348e+14 | 5.782721e+16 |
| -2.055600e+14 | -4.699358e+17 |
| -8.879634e+14 | 1.725658e+18 |
| -3.143035e+15 | 1.341364e+18 |
| -2.140738e+15 | 3.282851e+18 |
| -5.124384e+15 | -3.501109e+18 |
| -5.783538e+14 | 5.226449e+17 |
| -2.662185e+14 | 2.960134e+17 |
| -3.587970e+14 | 2.664019e+17 |
| -8.293654e+14 | 1.910528e+17 |
| -2.166597e+15 | 2.728096e+16 |
| -5.989545e+14 | 5.299203e+15 |
| -5.255729e+14 | -6.465461e+15 |
| -1.772479e+14 | -1.785856e+16 |
| -7.855557e+14 | 4.728051e+16 |
| -2.825954e+15 | -3.550280e+16 |
| -1.960934e+15 | 4.614577e+16 |
| -4.751271e+15 | -3.129732e+17 |
| -5.500825e+14 | -1.351002e+15 |
| -2.580479e+14 | 6.543024e+15 |
| -3.534380e+14 | -2.390021e+16 |
| -8.305629e+14 | 3.556885e+16 |
| -2.208807e+15 | -8.873823e+15 |
| -6.163100e+14 | 1.614397e+16 |
| -5.407620e+14 | 4.258829e+15 |
| -1.823575e+14 | -2.822178e+16 |
| -8.081470e+14 | 8.886674e+16 |
| -2.907030e+15 | 5.885773e+16 |
| -2.017058e+15 | 1.594877e+17 |
| -4.886935e+15 | -4.526878e+17 |
| -5.657518e+14 | -2.425026e+16 |
| -2.653811e+14 | 7.965293e+15 |
| -3.634582e+14 | 3.317085e+16 |
| -8.540544e+14 | 1.333236e+17 |
| -2.271134e+15 | 7.786586e+16 |
| -6.336598e+14 | 1.207802e+17 |
| -5.559495e+14 | 8.167438e+15 |
| -1.874671e+14 | -1.188927e+17 |
| -8.307383e+14 | 1.935112e+17 |
| -2.988105e+15 | 1.797900e+17 |
| -2.073182e+15 | 2.765459e+17 |
| -5.022598e+15 | -8.111040e+17 |
| -5.814210e+14 | -4.320238e+16 |
| -2.727143e+14 | -1.173363e+16 |
| -3.734785e+14 | 1.411738e+17 |
| -8.775460e+14 | 3.478245e+17 |
| -2.333461e+15 | -5.699310e+16 |
| -6.510097e+14 | 1.347844e+17 |
| -5.711369e+14 | 3.705689e+16 |
| -1.925772e+14 | -2.206366e+17 |
| -8.533377e+14 | 1.251808e+17 |
| -3.069228e+15 | 1.263916e+18 |
| -2.129353e+15 | 5.843621e+17 |
| -5.158404e+15 | -1.475031e+18 |
| -5.971087e+14 | -4.043338e+15 |
| -2.800592e+14 | -2.049579e+16 |
| -3.835167e+14 | 2.156059e+17 |
| -9.010841e+14 | 5.909461e+17 |
| -2.395924e+15 | 5.971857e+16 |
| -6.684015e+14 | 6.878142e+16 |
| -5.863644e+14 | -2.120065e+16 |
| -1.977003e+14 | -3.154358e+17 |
| -8.759828e+14 | 6.046929e+17 |
| -3.150478e+15 | 3.463842e+17 |
| -2.185585e+15 | 5.762971e+17 |
| -5.294297e+15 | -1.789629e+18 |
| -6.128025e+14 | 1.915486e+17 |
| -2.874007e+14 | 1.417621e+17 |
| -3.935464e+14 | 1.199709e+17 |
| -9.245934e+14 | -3.421189e+16 |
| -2.458285e+15 | 1.468806e+17 |
| -6.857569e+14 | 1.350992e+16 |
| -6.015535e+14 | 3.780932e+15 |
| -2.028099e+14 | 9.690814e+15 |
| -8.985741e+14 | 1.831663e+17 |
| -3.231554e+15 | -1.904705e+17 |
| -2.241709e+15 | 6.183858e+17 |
| -5.429960e+15 | -6.554704e+17 |
| -6.284718e+14 | -7.755610e+16 |
| -2.947339e+14 | -2.212961e+16 |
| -4.035666e+14 | 1.963152e+17 |
| -9.480850e+14 | 5.575824e+17 |
| -2.520612e+15 | -1.556952e+17 |
| -7.031068e+14 | 1.463043e+17 |
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
| NA | NA |
plot(SB.diff)
Including Plots
You can also embed plots, for example:
Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.