Home » date » 2010 » Apr » 29 »

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

*Unverified author*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Thu, 29 Apr 2010 12:51:08 +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/Apr/29/t1272545574hy1fwy56u0i50d2.htm/, Retrieved Thu, 29 Apr 2010 14:52:54 +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/Apr/29/t1272545574hy1fwy56u0i50d2.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:

KDGP2W21

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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.674596	8.0387	0
2	0.275832	3.2869	0.000638
3	0.022735	0.2709	0.393422
4	0.102027	1.2158	0.113041
5	0.384066	4.5767	5e-06
6	0.46496	5.5406	0
7	0.392595	4.6783	3e-06
8	0.098375	1.1723	0.121524
9	-0.006866	-0.0818	0.467453
10	0.196707	2.344	0.010231
11	0.532431	6.3447	0
12	0.79658	9.4924	0
13	0.525917	6.267	0
14	0.15697	1.8705	0.031735
15	-0.085484	-1.0187	0.155049
16	-0.019343	-0.2305	0.409016
17	0.227624	2.7125	0.003752
18	0.313804	3.7394	0.000133
19	0.265775	3.1671	0.000943
20	0.007686	0.0916	0.463578
21	-0.095582	-1.139	0.128312
22	0.080601	0.9605	0.169227
23	0.385136	4.5894	5e-06
24	0.618568	7.3711	0
25	0.388446	4.6289	4e-06
26	0.059917	0.714	0.238202
27	-0.160362	-1.9109	0.029014
28	-0.104848	-1.2494	0.106785
29	0.130049	1.5497	0.061719
30	0.201691	2.4034	0.008767
31	0.166261	1.9812	0.024748
32	-0.062623	-0.7462	0.228379
33	-0.160366	-1.911	0.029011
34	-0.001432	-0.0171	0.493204
35	0.269969	3.2171	0.000802
36	0.476626	5.6797	0
37	0.264686	3.1541	0.000983
38	-0.023886	-0.2846	0.388169
39	-0.202823	-2.4169	0.008461
40	-0.169249	-2.0168	0.022799
41	0.033043	0.3938	0.347176
42	0.092925	1.1073	0.135011
43	0.072155	0.8598	0.195666
44	-0.113115	-1.3479	0.089916
45	-0.193447	-2.3052	0.011302
46	-0.05519	-0.6577	0.255908
47	0.179239	2.1359	0.017202
48	0.363625	4.3331	1.4e-05

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.674596	8.0387	0
2	-0.328941	-3.9198	6.9e-05
3	-0.005443	-0.0649	0.474187
4	0.359597	4.2851	1.7e-05
5	0.342617	4.0827	3.7e-05
6	-0.16634	-1.9822	0.024695
7	0.142206	1.6946	0.046173
8	-0.239728	-2.8567	0.002462
9	0.22089	2.6322	0.004711
10	0.365052	4.3501	1.3e-05
11	0.321374	3.8296	9.6e-05
12	0.357154	4.256	1.9e-05
13	-0.49097	-5.8506	0
14	-0.054023	-0.6438	0.260385
15	-0.022641	-0.2698	0.393852
16	-0.12131	-1.4456	0.075249
17	-0.205039	-2.4433	0.00789
18	-0.009285	-0.1106	0.456026
19	0.036876	0.4394	0.330512
20	0.029606	0.3528	0.36238
21	-0.00615	-0.0733	0.470841
22	0.06615	0.7883	0.215927
23	0.085341	1.017	0.155451
24	0.055211	0.6579	0.25583
25	-0.086355	-1.029	0.152604
26	0.048014	0.5722	0.284062
27	0.028053	0.3343	0.369328
28	-0.061465	-0.7324	0.232554
29	0.040716	0.4852	0.314146
30	-0.167201	-1.9924	0.024121
31	0.028426	0.3387	0.367654
32	-0.016297	-0.1942	0.423149
33	-0.041781	-0.4979	0.309671
34	-0.001768	-0.0211	0.491612
35	0.013808	0.1645	0.434771
36	-0.014077	-0.1677	0.433511
37	-0.044747	-0.5332	0.297359
38	0.066058	0.7872	0.216245
39	0.093721	1.1168	0.13298
40	-0.166081	-1.9791	0.024871
41	-0.032163	-0.3833	0.35105
42	0.034585	0.4121	0.340435
43	0.015629	0.1862	0.426262
44	0.021141	0.2519	0.400732
45	-0.02679	-0.3192	0.375008
46	-0.013502	-0.1609	0.436204
47	0.049925	0.5949	0.276419
48	0.012894	0.1537	0.439052

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272545574hy1fwy56u0i50d2/1mhs71272545465.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272545574hy1fwy56u0i50d2/1mhs71272545465.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272545574hy1fwy56u0i50d2/2mhs71272545465.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Apr/29/t1272545574hy1fwy56u0i50d2/2mhs71272545465.ps (open in new window)

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

R code (references can be found in the software module):

if (par1 == 'Default') {

par1 = 10*log10(length(x))

} else {

par1 <- as.numeric(par1)

}

par2 <- as.numeric(par2)

par3 <- as.numeric(par3)

par4 <- as.numeric(par4)

par5 <- as.numeric(par5)

if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'

par7 <- as.numeric(par7)

if (par2 == 0) {

x <- log(x)

} else {

x <- (x ^ par2 - 1) / par2

}

if (par3 > 0) x <- diff(x,lag=1,difference=par3)

if (par4 > 0) x <- diff(x,lag=par5,difference=par4)

bitmap(file='pic1.png')

racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))

dev.off()

bitmap(file='pic2.png')

rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')

dev.off()

(myacf <- c(racf$acf))

(mypacf <- c(rpacf$acf))

lengthx <- length(x)

sqrtn <- sqrt(lengthx)

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Autocorrelation Function',4,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'Time lag k',header=TRUE)

a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)

a<-table.element(a,'T-STAT',header=TRUE)

a<-table.element(a,'P-value',header=TRUE)

a<-table.row.end(a)

for (i in 2:(par1+1)) {

a<-table.row.start(a)

a<-table.element(a,i-1,header=TRUE)

a<-table.element(a,round(myacf[i],6))

mytstat <- myacf[i]*sqrtn

a<-table.element(a,round(mytstat,4))

a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'Time lag k',header=TRUE)

a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)

a<-table.element(a,'T-STAT',header=TRUE)

a<-table.element(a,'P-value',header=TRUE)

a<-table.row.end(a)

for (i in 1:par1) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,round(mypacf[i],6))

mytstat <- mypacf[i]*sqrtn

a<-table.element(a,round(mytstat,4))

a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable1.tab')

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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