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AC Chocopasta

*The author of this computation has been verified*

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

Title produced by software: (Partial) Autocorrelation Function

Date of computation: Fri, 19 Dec 2008 06:28:10 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/19/t1229693415yqhpdflmo131xzh.htm/, Retrieved Fri, 19 Dec 2008 14:30:17 +0100

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/2008/Dec/19/t1229693415yqhpdflmo131xzh.htm/},
    year = {2008},
}
@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 = {2008},
    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:

Dataseries X:

» Textbox « » Textfile « » CSV «

101.73 101.63 101.43 101.34 101.01 100.89 100.93 100.77 100.3 99.86 99.71 99.93 99.88 99.92 99.87 99.63 100.05 99.88 100.11 100.05 100.07 100.2 100.21 99.76 99.41 99.24 99.65 99.7 99.79 99.84 101 101.62 101.98 101.46 102.28 102.14 102.02 102.21 101.61 102.38 102.19 102.04 101.76 101.9 102.01 102.37 103.04 103.42 103.76 104.41 104.75 104.28 103.89 104.09 103.8 105.03 105.86 106.04 106.03 106.13 107.21 107.66 108.08 108.76 108.26 108.71 108.65 108.61 108.86 109.54 108.22 108.77 109.9 110.13 109.6 110.42 110.6 109.73 110.72 111.08 111.14 111.01 110.56 111.57

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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.046118	-0.4202	0.337729
2	-0.084984	-0.7742	0.220494
3	0.114546	1.0436	0.149859
4	0.066894	0.6094	0.271952
5	-0.011796	-0.1075	0.45734
6	0.026567	0.242	0.404676
7	0.09199	0.8381	0.202199
8	-0.106453	-0.9698	0.167474
9	-0.021225	-0.1934	0.423572
10	0.051549	0.4696	0.319925
11	0.022869	0.2083	0.417736
12	0.104866	0.9554	0.171081
13	0.044239	0.403	0.343979
14	0.001781	0.0162	0.493545
15	0.030704	0.2797	0.390191
16	0.238808	2.1756	0.016213
17	-0.028883	-0.2631	0.396548
18	0.08973	0.8175	0.207997
19	0.045005	0.41	0.341426
20	-0.055618	-0.5067	0.306854
21	-0.113601	-1.035	0.151849
22	-0.15618	-1.4229	0.079262
23	0.144891	1.32	0.095229
24	-0.07507	-0.6839	0.247966
25	-0.016496	-0.1503	0.440453
26	0.076982	0.7013	0.242525
27	-0.098516	-0.8975	0.186017
28	0.079613	0.7253	0.235151
29	0.101886	0.9282	0.177992
30	0.0646	0.5885	0.278885
31	-0.074518	-0.6789	0.249549
32	0.00816	0.0743	0.470459
33	0.014966	0.1364	0.445937
34	0.009917	0.0903	0.464115
35	0.007204	0.0656	0.473916
36	-0.109485	-0.9975	0.16072
37	0.01315	0.1198	0.452466
38	-0.081176	-0.7395	0.23083
39	0.032559	0.2966	0.383747
40	-0.152833	-1.3924	0.083765
41	0.047798	0.4355	0.332178
42	0.00501	0.0456	0.48185
43	-0.09011	-0.8209	0.207015
44	0.077294	0.7042	0.241646
45	-0.045788	-0.4171	0.338824
46	-0.045627	-0.4157	0.339357
47	-0.056702	-0.5166	0.303412
48	-0.078826	-0.7181	0.237345
49	0.05675	0.517	0.30326
50	-0.052471	-0.478	0.316942
51	-0.081974	-0.7468	0.228642
52	-0.07729	-0.7041	0.241656
53	0.014085	0.1283	0.449103
54	-0.074885	-0.6822	0.248495
55	-0.041052	-0.374	0.354678
56	-0.03838	-0.3497	0.36374
57	0.011983	0.1092	0.456665
58	-0.032227	-0.2936	0.384898
59	-0.044175	-0.4025	0.344193
60	-0.020849	-0.1899	0.424909

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.046118	-0.4202	0.337729
2	-0.087296	-0.7953	0.214352
3	0.107303	0.9776	0.165562
4	0.071053	0.6473	0.259604
5	0.013143	0.1197	0.452489
6	0.02581	0.2351	0.407339
7	0.081287	0.7406	0.230525
8	-0.102194	-0.931	0.177269
9	-0.024545	-0.2236	0.411804
10	0.011839	0.1079	0.457183
11	0.034388	0.3133	0.377424
12	0.135086	1.2307	0.110958
13	0.057908	0.5276	0.299602
14	0.0135	0.123	0.451205
15	0.027239	0.2482	0.402312
16	0.219521	1.9999	0.024389
17	-0.023468	-0.2138	0.415614
18	0.124311	1.1325	0.130338
19	-0.011381	-0.1037	0.458836
20	-0.046817	-0.4265	0.335417
21	-0.144162	-1.3134	0.096337
22	-0.246293	-2.2438	0.013753
23	0.070462	0.6419	0.261342
24	-0.04514	-0.4112	0.340976
25	0.048619	0.4429	0.32948
26	0.090541	0.8249	0.205905
27	-0.094313	-0.8592	0.196344
28	0.05958	0.5428	0.294361
29	0.063738	0.5807	0.281513
30	0.019462	0.1773	0.429848
31	-0.059804	-0.5448	0.293661
32	-0.059163	-0.539	0.295665
33	-0.004349	-0.0396	0.484246
34	0.0281	0.256	0.39929
35	-0.011906	-0.1085	0.456943
36	-0.103466	-0.9426	0.174305
37	0.108725	0.9905	0.162396
38	0.005064	0.0461	0.481658
39	0.054345	0.4951	0.310916
40	-0.141541	-1.2895	0.100403
41	-0.036306	-0.3308	0.370828
42	-0.0869	-0.7917	0.215398
43	-0.065208	-0.5941	0.277039
44	-0.014374	-0.131	0.448065
45	-0.047335	-0.4312	0.333704
46	-0.074007	-0.6742	0.251018
47	-0.016802	-0.1531	0.439355
48	-0.104558	-0.9526	0.171788
49	0.060499	0.5512	0.291497
50	0.075524	0.6881	0.246667
51	-0.035752	-0.3257	0.372729
52	-0.022639	-0.2062	0.41855
53	-0.05535	-0.5043	0.307706
54	-0.053189	-0.4846	0.314627
55	-0.026354	-0.2401	0.405423
56	-0.003988	-0.0363	0.485551
57	0.012338	0.1124	0.455388
58	0.036992	0.337	0.368478
59	0.039123	0.3564	0.361214
60	-0.060773	-0.5537	0.290647

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229693415yqhpdflmo131xzh/14yda1229693288.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229693415yqhpdflmo131xzh/14yda1229693288.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229693415yqhpdflmo131xzh/2iliy1229693288.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229693415yqhpdflmo131xzh/2iliy1229693288.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')

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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