Home » date » 2010 » May » 18 »

The total generation of electricity by the U.S. electric industry

*Unverified author*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Tue, 18 May 2010 15:53:03 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y.htm/, Retrieved Tue, 18 May 2010 17:58:45 +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/2010/May/18/t12741983197qrut8cjkbqjt9y.htm/},
    year = {2010},
}
@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 = {2010},
    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:
KDGP2W52
 
Dataseries X:
» Textbox « » Textfile « » CSV «
227.86 198.24 194.97 184.88 196.79 205.36 226.72 226.05 202.50 194.79 192.43 219.25 217.47 192.34 196.83 186.07 197.31 215.02 242.67 225.17 206.69 197.75 196.43 213.55 222.75 194.03 201.85 189.50 206.07 225.59 247.91 247.64 213.01 203.01 200.26 220.50 237.90 216.94 214.01 196.00 208.37 232.75 257.46 267.69 220.18 210.61 209.59 232.75 232.75 219.82 226.74 208.04 220.12 235.69 257.05 258.69 227.15 219.91 219.30 259.04 237.29 212.88 226.03 211.07 222.91 249.18 266.38 268.53 238.02 224.69 213.75 237.43 248.46 210.82 221.40 209.00 234.37 248.43 271.98 268.11 233.88 223.43 221.38 233.76 243.97 217.76 224.66 210.84 220.35 236.84 266.15 255.20 234.76 221.29 221.26 244.13 245.78 224.62 234.80 211.37 222.39 249.63 282.29 279.13 236.60 223.62 225.86 246.41 261.70 225.01 231.54 214.82 227.70 263.86 278.15 274.64 237.66 227.97 224.75 242.91 253.08 228.13 233.68 217.38 236.38 256.08 292.83 304.71 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1227.86NANA11.0968263888889NA
2198.24NANA-15.3863819444444NA
3194.97NANA-8.97459027777778NA
4184.88NANA-25.0641319444444NA
5196.79NANA-11.2149236111111NA
6205.36NANA10.1592013888889NA
7226.72240.150826388889205.38708333333334.7637430555556-13.4308263888889
8226.05237.702076388889204.70833333333332.9937430555555-11.6520763888888
9202.5201.503034722222204.54-3.036965277777780.996965277777775
10194.79190.568701388889204.667083333333-14.09838194444444.22129861111105
11192.43188.247034722222204.738333333333-16.49129861111114.18296527777781
12219.25210.415659722222205.16255.253159722222248.83434027777776
13217.47217.326409722222206.22958333333311.09682638888890.143590277777776
14192.34191.471118055556206.8575-15.38638194444440.868881944444496
15196.83198.020826388889206.995416666667-8.97459027777778-1.19082638888887
16186.07182.229201388889207.293333333333-25.06413194444443.84079861111113
17197.31196.368409722222207.583333333333-11.21492361111110.941590277777777
18215.02217.671701388889207.512510.1592013888889-2.65170138888885
19242.67242.258743055556207.49534.76374305555560.41125694444446
20225.17240.779159722222207.78541666666732.9937430555555-15.6091597222222
21206.69205.028034722222208.065-3.036965277777781.66196527777782
22197.75194.318701388889208.417083333333-14.09838194444443.43129861111115
23196.43192.433701388889208.925-16.49129861111113.99629861111117
24213.55214.983576388889209.7304166666675.25315972222224-1.43357638888884
25222.75221.485993055556210.38916666666711.09682638888891.26400694444445
26194.03196.157368055556211.54375-15.3863819444444-2.12736805555556
27201.85203.768743055556212.743333333333-8.97459027777778-1.91874305555558
28189.5188.161701388889213.225833333333-25.06413194444441.33829861111113
29206.07202.389659722222213.604583333333-11.21492361111113.68034027777782
30225.59224.212951388889214.0537510.15920138888891.37704861111115
31247.91249.738326388889214.97458333333334.7637430555556-1.82832638888888
32247.64249.554159722222216.56041666666732.9937430555555-1.91415972222222
33213.01214.984701388889218.021666666667-3.03696527777778-1.97470138888886
34203.01204.700784722222218.799166666667-14.0983819444444-1.69078472222222
35200.26202.674534722222219.165833333333-16.4912986111111-2.41453472222219
36220.5224.813159722222219.565.25315972222224-4.31315972222220
37237.9231.353076388889220.2562511.09682638888896.54692361111114
38216.94206.103201388889221.489583333333-15.386381944444410.8367986111112
39214.01213.649159722222222.62375-8.974590277777780.360840277777783
40196198.175034722222223.239166666667-25.0641319444444-2.17503472222216
41208.37212.729659722222223.944583333333-11.2149236111111-4.35965972222220
42232.75235.002951388889224.8437510.1592013888889-2.25295138888890
43257.46259.903326388889225.13958333333334.7637430555556-2.44332638888889
44267.69258.038743055556225.04532.99374305555559.65125694444444
45220.18222.658451388889225.695416666667-3.03696527777778-2.47845138888891
46210.61212.629118055556226.7275-14.0983819444444-2.01911805555557
47209.59211.227451388889227.71875-16.4912986111111-1.63745138888888
48232.75233.583993055556228.3308333333335.25315972222224-0.83399305555551
49232.75239.533076388889228.4362511.0968263888889-6.7830763888889
50219.82212.657784722222228.044166666667-15.38638194444447.16221527777776
51226.74218.984993055556227.959583333333-8.974590277777787.7550069444444
52208.04203.573368055556228.6375-25.06413194444444.46663194444443
53220.12218.214659722222229.429583333333-11.21492361111111.90534027777778
54235.69241.088784722222230.92958333333310.1592013888889-5.39878472222225
55257.05266.977909722222232.21416666666734.7637430555556-9.92790972222218
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59219.3215.643284722222232.134583333333-16.49129861111113.65671527777778
60259.04238.066076388889232.8129166666675.2531597222222420.9739236111111
61237.29244.860576388889233.7637511.0968263888889-7.57057638888892
62212.88219.176118055556234.5625-15.3863819444444-6.29611805555555
63226.03226.450826388889235.425416666667-8.97459027777778-0.420826388888912
64211.07211.013368055556236.0775-25.06413194444440.0566319444444332
65222.91224.830493055556236.045416666667-11.2149236111111-1.92049305555557
66249.18245.072951388889234.9137510.15920138888894.10704861111111
67266.38269.242493055556234.4787534.7637430555556-2.86249305555552
68268.53267.852076388889234.85833333333332.99374305555550.67792361111114
69238.02231.542618055556234.579583333333-3.036965277777786.47738194444446
70224.69220.202034722222234.300416666667-14.09838194444444.48796527777785
71213.75218.200368055556234.691666666667-16.4912986111111-4.45036805555554
72237.43240.391076388889235.1379166666675.25315972222224-2.96107638888884
73248.46246.436826388889235.3411.09682638888892.02317361111113
74210.82220.169451388889235.555833333333-15.3863819444444-9.34945138888887
75221.4226.391243055556235.365833333333-8.97459027777778-4.99124305555554
76209210.076701388889235.140833333333-25.0641319444444-1.07670138888886
77234.37224.191326388889235.40625-11.214923611111110.1786736111112
78248.43245.730451388889235.5712510.15920138888892.69954861111114
79271.98269.994993055556235.2312534.76374305555561.98500694444451
80268.11268.327076388889235.33333333333332.9937430555555-0.217076388888813
81233.88232.721368055556235.758333333333-3.036965277777781.15863194444447
82223.43221.872451388889235.970833333333-14.09838194444441.55754861111114
83221.38218.972034722222235.463333333333-16.49129861111112.40796527777781
84233.76239.649409722222234.396255.25315972222224-5.88940972222221
85243.97244.767243055556233.67041666666711.0968263888889-0.797243055555555
86217.76217.503201388889232.889583333333-15.38638194444440.256798611111151
87224.66223.413743055556232.388333333333-8.974590277777781.24625694444447
88210.84207.271701388889232.335833333333-25.06413194444443.56829861111115
89220.35221.026743055555232.241666666667-11.2149236111111-0.676743055555505
90236.84242.827951388889232.6687510.1592013888889-5.98795138888886
91266.15267.939993055556233.1762534.7637430555556-1.78999305555556
92255.2266.531243055556233.537532.9937430555555-11.3312430555555
93234.76231.208868055556234.245833333333-3.036965277777783.55113194444442
94221.29220.592034722222234.690416666667-14.09838194444440.697965277777769
95221.26218.306201388889234.7975-16.49129861111112.95379861111113
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97245.78247.717659722222236.62083333333311.0968263888889-1.93765972222224
98224.62222.904034722222238.290416666667-15.38638194444441.71596527777783
99234.8230.389576388889239.364166666667-8.974590277777784.41042361111113
100211.37214.473784722222239.537916666667-25.0641319444444-3.10378472222217
101222.39228.611743055556239.826666666667-11.2149236111111-6.22174305555555
102249.63250.272534722222240.11333333333310.1592013888889-0.642534722222251
103282.29275.635409722222240.87166666666734.76374305555566.6545902777778
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107225.86225.313284722222241.804583333333-16.49129861111110.546715277777821
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109261.7254.135993055556243.03916666666711.09682638888897.56400694444449
110225.01227.293201388889242.679583333333-15.3863819444444-2.28320138888884
111231.54233.562076388889242.536666666667-8.97459027777778-2.02207638888885
112214.82217.697951388889242.762083333333-25.0641319444444-2.87795138888885
113227.7231.682159722222242.897083333333-11.2149236111111-3.98215972222221
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119224.75226.362868055556242.854166666667-16.4912986111111-1.61286805555557
120242.91248.144826388889242.8916666666675.25315972222224-5.2348263888889
121253.08254.275993055556243.17916666666711.0968263888889-1.19599305555553
122228.13229.657368055556245.04375-15.3863819444444-1.52736805555554
123233.68237.651659722222246.62625-8.97459027777778-3.97165972222223
124217.38222.160034722222247.224166666667-25.0641319444444-4.78003472222218
125236.38236.667993055556247.882916666667-11.2149236111111-0.287993055555546
126256.08259.068368055556248.90916666666710.1592013888889-2.98836805555555
127292.83284.957909722222250.19416666666734.76374305555567.8720902777778
128304.71284.552909722222251.55916666666732.993743055555520.1570902777777
129245.57249.812618055556252.849583333333-3.03696527777778-4.24261805555557
130234.41239.695368055556253.79375-14.0983819444444-5.28536805555555
131234.12238.309118055556254.800416666667-16.4912986111111-4.18911805555555
132258.17261.220243055555255.9670833333335.25315972222224-3.05024305555548
133268.66NA256.334583333333NANA
134245.31NA255.56625NANA
135247.47NA255.173333333333NANA
136226.25NA255.652916666667NANA
137251.67NANANANA
138268.79NANANANA
139288.94NANANANA
140290.16NANANANA
141250.69NANANANA
142240.8NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/1fw5i1274197981.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/1fw5i1274197981.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/2fw5i1274197981.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/2fw5i1274197981.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/3pnnk1274197981.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/3pnnk1274197981.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/4n0bu1274197981.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/18/t12741983197qrut8cjkbqjt9y/4n0bu1274197981.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')
 




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