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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: Wed, 05 May 2010 15:57:18 +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/05/t1273075083qv0k7udn2vohzyx.htm/, Retrieved Wed, 05 May 2010 17:58:05 +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/05/t1273075083qv0k7udn2vohzyx.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 «

2953 2635 2404 2413 2136 1565 1451 2037 2477 2785 2994 2681 3098 2708 2517 2445 2087 1801 1216 2173 2286 3121 3458 3511 3524 2767 2744 2603 2527 1846 1066 2327 3066 3048 3806 4042 3583 3438 2957 2885 2744 1837 1447 2504 3248 3098 4318 3561 3316 3379 2717 2354 2445 1542 1606 2590 3588 3202 4704 4005 3810 3488 2781 2944 2817 1960 1937 2903 3357 3552 4581 3905 4581 4037 3345 3175 2808 2050 1719 3143 3756 4776 4540 4309 4563 3506 3665 3361 3094 2440 1633 2935 4159 4159 4894 4921 4577 4155 3851 3429 3370 2726

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	0.08354	0.8396	0.201567
2	0.038231	0.3842	0.350813
3	0.053865	0.5413	0.294732
4	-0.257699	-2.5898	0.00551
5	-0.24387	-2.4509	0.007985
6	-0.26514	-2.6646	0.004487
7	-0.279919	-2.8132	0.002948
8	-0.181865	-1.8277	0.035272
9	0.051558	0.5182	0.302741
10	-0.05896	-0.5925	0.277405
11	0.23013	2.3128	0.011382
12	0.689564	6.93	0
13	0.120479	1.2108	0.114399
14	0.105883	1.0641	0.144908
15	-0.016621	-0.167	0.433838
16	-0.175401	-1.7628	0.040483
17	-0.24294	-2.4415	0.008182
18	-0.236509	-2.3769	0.009672
19	-0.258401	-2.5969	0.005405
20	-0.146164	-1.4689	0.072479
21	0.045467	0.4569	0.32435
22	-0.030289	-0.3044	0.380726
23	0.264578	2.659	0.004558
24	0.490068	4.9251	2e-06
25	0.187584	1.8852	0.031139
26	0.010358	0.1041	0.458648
27	-0.02833	-0.2847	0.388225
28	-0.115714	-1.1629	0.123804
29	-0.210175	-2.1122	0.018566
30	-0.194164	-1.9513	0.026894
31	-0.227479	-2.2861	0.012167
32	-0.09774	-0.9823	0.164156
33	0.00102	0.0103	0.49592
34	0.001123	0.0113	0.495507
35	0.216303	2.1738	0.016027
36	0.383322	3.8523	0.000103
37	0.210016	2.1106	0.018636
38	-0.024147	-0.2427	0.404376
39	-0.032448	-0.3261	0.372513
40	-0.100565	-1.0107	0.157296
41	-0.170305	-1.7115	0.045025
42	-0.158917	-1.5971	0.056684
43	-0.172089	-1.7295	0.04339
44	-0.071119	-0.7147	0.238211
45	-0.02858	-0.2872	0.387265
46	0.083778	0.842	0.2009
47	0.108312	1.0885	0.139477
48	0.333321	3.3498	0.000569

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.08354	0.8396	0.201567
2	0.031472	0.3163	0.376219
3	0.048529	0.4877	0.313405
4	-0.269861	-2.7121	0.00393
5	-0.22019	-2.2129	0.014578
6	-0.252359	-2.5362	0.006369
7	-0.271498	-2.7285	0.003752
8	-0.301012	-3.0251	0.001576
9	-0.141915	-1.4262	0.078442
10	-0.406061	-4.0809	4.5e-05
11	-0.246424	-2.4765	0.007464
12	0.473934	4.763	3e-06
13	0.108267	1.0881	0.139577
14	-0.035954	-0.3613	0.359301
15	-0.157335	-1.5812	0.05848
16	0.068383	0.6872	0.246754
17	-0.050141	-0.5039	0.307709
18	0.0095	0.0955	0.462064
19	-0.012677	-0.1274	0.449437
20	-0.049986	-0.5023	0.308258
21	0.000686	0.0069	0.497258
22	0.082217	0.8263	0.2053
23	0.031228	0.3138	0.377147
24	-0.015162	-0.1524	0.439596
25	0.084045	0.8446	0.200155
26	-0.172786	-1.7365	0.042764
27	-0.103679	-1.042	0.149959
28	0.026983	0.2712	0.393405
29	0.118661	1.1925	0.117925
30	-0.010193	-0.1024	0.459307
31	0.00763	0.0767	0.469513
32	0.037228	0.3741	0.354542
33	-0.055355	-0.5563	0.289615
34	-0.031596	-0.3175	0.375744
35	-0.054996	-0.5527	0.290845
36	-0.061072	-0.6138	0.270376
37	0.002705	0.0272	0.489184
38	0.053997	0.5427	0.294277
39	-0.04607	-0.463	0.32218
40	-0.045953	-0.4618	0.322601
41	-0.00072	-0.0072	0.497121
42	0.0213	0.2141	0.415464
43	-0.020951	-0.2106	0.41683
44	-0.001514	-0.0152	0.493946
45	-0.061984	-0.6229	0.267366
46	0.115492	1.1607	0.124255
47	-0.039257	-0.3945	0.347011
48	0.031954	0.3211	0.374388

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/05/t1273075083qv0k7udn2vohzyx/1iduq1273075036.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273075083qv0k7udn2vohzyx/1iduq1273075036.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273075083qv0k7udn2vohzyx/2bmtb1273075036.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/05/t1273075083qv0k7udn2vohzyx/2bmtb1273075036.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; 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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