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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 03:57:15 -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/t1229684300vxloqzvukyy1zn7.htm/, Retrieved Fri, 19 Dec 2008 11:58:25 +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/t1229684300vxloqzvukyy1zn7.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 «

101.7 101.9 102 102.2 102.4 102.6 102.6 102.5 102.5 102.6 102.7 102.9 103.1 103.2 103.2 103 102.8 102.6 102.4 102.2 101.9 101.6 101.3 101.2 111.7 111.4 111.1 111.1 111.3 111.9 112.4 112.9 113 113 112.7 112.4 112.3 112.5 112.8 113.2 114 114.9 115.6 115.5 115 114.9 115.2 115.4 115 114.6 114.5 114.4 113.9 113.2 112.7 112.6 112.5 112.3 112 111.7 119.2

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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.028771	-0.2229	0.4122
2	-0.05796	-0.449	0.327539
3	-0.043968	-0.3406	0.367307
4	-0.026819	-0.2077	0.418068
5	0.003388	0.0262	0.489575
6	-0.026999	-0.2091	0.417527
7	-0.039884	-0.3089	0.37922
8	-0.053062	-0.411	0.341264
9	-0.036668	-0.284	0.388682
10	-0.044453	-0.3443	0.3659
11	-0.058804	-0.4555	0.325199
12	-0.046596	-0.3609	0.359709
13	-0.002948	-0.0228	0.490928
14	0.001306	0.0101	0.49598
15	-0.010778	-0.0835	0.466872
16	-0.010077	-0.0781	0.46902
17	0.008538	0.0661	0.473746
18	0.039421	0.3054	0.380577
19	0.00966	0.0748	0.4703
20	-0.022193	-0.1719	0.432045
21	-0.016044	-0.1243	0.450754
22	-0.000929	-0.0072	0.497142
23	-0.004309	-0.0334	0.486741
24	-0.048952	-0.3792	0.352945
25	-0.056896	-0.4407	0.330501
26	-0.035005	-0.2711	0.393604
27	-0.019034	-0.1474	0.44164
28	-0.038401	-0.2975	0.383574
29	-0.033515	-0.2596	0.398028
30	-0.020711	-0.1604	0.436542
31	0.010406	0.0806	0.468013
32	-0.006122	-0.0474	0.481167
33	-0.021433	-0.166	0.43435
34	-0.042504	-0.3292	0.371561
35	-0.043698	-0.3385	0.368091
36	0.45866	3.5528	0.000375
37	0.003151	0.0244	0.490304
38	-0.007686	-0.0595	0.476363
39	-0.010644	-0.0824	0.467283
40	-0.012369	-0.0958	0.461995
41	-0.007776	-0.0602	0.476084
42	-0.007891	-0.0611	0.475732
43	-0.009577	-0.0742	0.470557
44	-0.011362	-0.088	0.465082
45	-0.012272	-0.0951	0.462294
46	-0.003658	-0.0283	0.488746
47	-0.000298	-0.0023	0.499083
48	0.00261	0.0202	0.49197
49	0.001933	0.015	0.494051
50	-0.002397	-0.0186	0.492625
51	-0.002546	-0.0197	0.492165
52	-0.007985	-0.0618	0.475444
53	-0.014124	-0.1094	0.456623
54	-0.010963	-0.0849	0.466304
55	-0.002518	-0.0195	0.492251
56	-0.002673	-0.0207	0.491776
57	-0.002941	-0.0228	0.490949
58	-0.007918	-0.0613	0.47565
59	-0.003941	-0.0305	0.487873
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.028771	-0.2229	0.4122
2	-0.058837	-0.4557	0.325108
3	-0.047631	-0.3689	0.356734
4	-0.033365	-0.2584	0.398475
5	-0.004102	-0.0318	0.487378
6	-0.033024	-0.2558	0.399489
7	-0.045188	-0.35	0.363772
8	-0.06141	-0.4757	0.318016
9	-0.049916	-0.3866	0.350193
10	-0.062372	-0.4831	0.31538
11	-0.079428	-0.6153	0.270358
12	-0.072084	-0.5584	0.289339
13	-0.032441	-0.2513	0.401225
14	-0.029028	-0.2249	0.411429
15	-0.038481	-0.2981	0.383339
16	-0.036866	-0.2856	0.388097
17	-0.019819	-0.1535	0.439252
18	0.009776	0.0757	0.469944
19	-0.016115	-0.1248	0.450539
20	-0.044137	-0.3419	0.366816
21	-0.039332	-0.3047	0.380838
22	-0.028476	-0.2206	0.413087
23	-0.033315	-0.2581	0.398622
24	-0.075042	-0.5813	0.281617
25	-0.085141	-0.6595	0.256049
26	-0.072636	-0.5626	0.28789
27	-0.06576	-0.5094	0.306178
28	-0.089696	-0.6948	0.244937
29	-0.088274	-0.6838	0.248378
30	-0.085238	-0.6603	0.25581
31	-0.066559	-0.5156	0.304026
32	-0.091477	-0.7086	0.240665
33	-0.113117	-0.8762	0.192208
34	-0.152094	-1.1781	0.121701
35	-0.188101	-1.457	0.075162
36	0.358343	2.7757	0.003668
37	-0.043787	-0.3392	0.367832
38	-0.018108	-0.1403	0.444461
39	-0.025581	-0.1982	0.421799
40	-0.039641	-0.3071	0.37993
41	-0.066409	-0.5144	0.304431
42	-0.042838	-0.3318	0.37059
43	-0.035912	-0.2782	0.390918
44	-0.022634	-0.1753	0.43071
45	-0.033838	-0.2621	0.397069
46	-0.010754	-0.0833	0.466944
47	0.013159	0.1019	0.459578
48	0.015548	0.1204	0.45227
49	-0.018391	-0.1425	0.443597
50	-0.025666	-0.1988	0.421542
51	-0.016912	-0.131	0.448107
52	-0.027547	-0.2134	0.415879
53	-0.050416	-0.3905	0.348766
54	-0.080367	-0.6225	0.26798
55	-0.052468	-0.4064	0.34294
56	-0.024034	-0.1862	0.426471
57	-0.027739	-0.2149	0.415301
58	-0.044837	-0.3473	0.364788
59	-0.039066	-0.3026	0.381619
60	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684300vxloqzvukyy1zn7/1mdc31229684233.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684300vxloqzvukyy1zn7/1mdc31229684233.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684300vxloqzvukyy1zn7/2w6wy1229684233.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229684300vxloqzvukyy1zn7/2w6wy1229684233.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 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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