Home » date » 2008 » Dec » 17 »

cor met lamda = 1

*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: Wed, 17 Dec 2008 08:51:34 -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/17/t1229529178l66786u2pvw2cur.htm/, Retrieved Wed, 17 Dec 2008 16:52:58 +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/17/t1229529178l66786u2pvw2cur.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 «

7.8 7.6 7.5 7.6 7.5 7.3 7.6 7.5 7.6 7.9 7.9 8.1 8.2 8.0 7.5 6.8 6.5 6.6 7.6 8.0 8.0 7.7 7.5 7.6 7.7 7.9 7.8 7.5 7.5 7.1 7.5 7.5 7.6 7.7 7.7 7.9 8.1 8.2 8.2 8.1 7.9 7.3 6.9 6.6 6.7 6.9 7.0 7.1 7.2 7.1 6.9 7.0 6.8 6.4 6.7 6.7 6.4 6.3 6.2 6.5 6.8 6.8 6.5 6.3 5.9 5.9 6.4 6.4

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	0.348149	2.8497	0.002904
2	-0.060731	-0.4971	0.310372
3	-0.318682	-2.6085	0.005602
4	-0.440418	-3.605	0.000298
5	-0.143472	-1.1744	0.122203
6	0.056012	0.4585	0.324045
7	0.080291	0.6572	0.256649
8	-0.069147	-0.566	0.286645
9	-0.081715	-0.6689	0.25294
10	-0.071406	-0.5845	0.280428
11	-0.014035	-0.1149	0.454442
12	0.278086	2.2762	0.013017
13	0.063296	0.5181	0.303048
14	0.159837	1.3083	0.097617
15	0.094487	0.7734	0.221
16	-0.075146	-0.6151	0.270287
17	-0.12596	-1.031	0.153118
18	-0.127388	-1.0427	0.150415
19	-0.020957	-0.1715	0.432157
20	-0.035432	-0.29	0.386348
21	0.049135	0.4022	0.344413
22	-0.018389	-0.1505	0.440403
23	-0.16741	-1.3703	0.087582
24	-0.018653	-0.1527	0.439555
25	-0.062228	-0.5094	0.306086
26	0.133353	1.0915	0.139472
27	0.190904	1.5626	0.061428
28	0.103839	0.85	0.199187
29	0.07191	0.5886	0.279051
30	-0.031626	-0.2589	0.398263
31	-0.111959	-0.9164	0.181366
32	-0.175164	-1.4338	0.078143
33	-0.092683	-0.7586	0.225365
34	-0.074808	-0.6123	0.271195
35	0.029626	0.2425	0.404566
36	0.171979	1.4077	0.08192
37	0.019801	0.1621	0.435866
38	-0.03983	-0.326	0.372712
39	-0.081737	-0.669	0.252881
40	0.006821	0.0558	0.477822
41	0.144199	1.1803	0.121023
42	0.162163	1.3274	0.094447
43	0.022793	0.1866	0.426281
44	-0.195661	-1.6016	0.05698
45	-0.165067	-1.3511	0.090599
46	-0.120832	-0.9891	0.163098
47	0.027598	0.2259	0.410985
48	0.234647	1.9207	0.029515
49	0.103588	0.8479	0.199755
50	-0.007604	-0.0622	0.475279
51	-0.022495	-0.1841	0.427235
52	-0.05642	-0.4618	0.322855
53	-0.053915	-0.4413	0.330203
54	0.004707	0.0385	0.48469
55	-0.00652	-0.0534	0.478798
56	-0.013756	-0.1126	0.455343
57	0.043615	0.357	0.361104
58	-0.015926	-0.1304	0.448336
59	-0.008537	-0.0699	0.47225
60	0.037605	0.3078	0.379591

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.348149	2.8497	0.002904
2	-0.207033	-1.6946	0.047394
3	-0.262841	-2.1515	0.017525
4	-0.304206	-2.49	0.00763
5	0.054868	0.4491	0.327398
6	-0.052257	-0.4277	0.335105
7	-0.147979	-1.2113	0.115025
8	-0.291026	-2.3822	0.010029
9	-0.04368	-0.3575	0.360908
10	-0.110588	-0.9052	0.184301
11	-0.151799	-1.2425	0.109186
12	0.159678	1.307	0.097837
13	-0.27445	-2.2465	0.013987
14	0.266707	2.1831	0.016269
15	0.015384	0.1259	0.450086
16	0.060279	0.4934	0.31167
17	-0.134615	-1.1019	0.13723
18	0.139616	1.1428	0.128593
19	0.110921	0.9079	0.183584
20	-0.045449	-0.372	0.355527
21	0.029207	0.2391	0.405891
22	-0.04861	-0.3979	0.345989
23	-0.096927	-0.7934	0.215179
24	-0.065987	-0.5401	0.295451
25	-0.069737	-0.5708	0.285015
26	-0.091003	-0.7449	0.229472
27	-0.006477	-0.053	0.478938
28	-0.061203	-0.501	0.309018
29	0.094965	0.7773	0.219853
30	-0.062403	-0.5108	0.305587
31	-0.087494	-0.7162	0.238187
32	-0.032691	-0.2676	0.394918
33	-0.072809	-0.596	0.276602
34	-0.100252	-0.8206	0.207392
35	0.1071	0.8767	0.191903
36	0.011982	0.0981	0.461081
37	-0.037813	-0.3095	0.378945
38	-0.144715	-1.1845	0.120191
39	0.01069	0.0875	0.465268
40	0.082941	0.6789	0.249769
41	-0.038212	-0.3128	0.377711
42	0.037234	0.3048	0.380743
43	-0.129474	-1.0598	0.146523
44	-0.083164	-0.6807	0.249195
45	0.016287	0.1333	0.447171
46	-0.041501	-0.3397	0.367571
47	-0.11946	-0.9778	0.165841
48	0.116376	0.9526	0.172114
49	-0.017357	-0.1421	0.443723
50	-0.002455	-0.0201	0.492015
51	0.062513	0.5117	0.305276
52	0.028953	0.237	0.406695
53	-0.010391	-0.0851	0.466237
54	-0.092762	-0.7593	0.225171
55	-0.009971	-0.0816	0.467597
56	0.001698	0.0139	0.494477
57	-0.072274	-0.5916	0.278058
58	0.013092	0.1072	0.45749
59	0.04029	0.3298	0.371295
60	-0.054458	-0.4458	0.328604

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t1229529178l66786u2pvw2cur/15rvd1229529089.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t1229529178l66786u2pvw2cur/15rvd1229529089.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t1229529178l66786u2pvw2cur/24gks1229529089.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/17/t1229529178l66786u2pvw2cur/24gks1229529089.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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