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ws acf

*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, 10 Dec 2010 19:01:40 +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/Dec/10/t1292007582iosz5cmj8xy676z.htm/, Retrieved Fri, 10 Dec 2010 19:59:44 +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/2010/Dec/10/t1292007582iosz5cmj8xy676z.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

1576.23 1546.37 1545.05 1552.34 1594.3 1605.78 1673.21 1612.94 1566.34 1530.17 1582.54 1702.16 1701.93 1811.15 1924.2 2034.25 2011.13 2013.04 2151.67 1902.09 1944.01 1916.67 1967.31 2119.88 2216.38 2522.83 2647.64 2631.23 2693.41 3021.76 2953.67 2796.8 2672.05 2251.23 2046.08 2420.04 2608.89 2660.47 2493.98 2541.7 2554.6 2699.61 2805.48 2956.66 3149.51 3372.5 3379.33 3517.54 3527.34 3281.06 3089.65 3222.76 3165.76 3232.43 3229.54 3071.74 2850.17

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.951752	7.1856	0
2	0.880781	6.6498	0
3	0.807489	6.0964	0
4	0.736325	5.5591	0
5	0.673733	5.0866	2e-06
6	0.617173	4.6596	1e-05
7	0.560909	4.2348	4.2e-05
8	0.495817	3.7433	0.000212
9	0.432245	3.2634	0.000932
10	0.375064	2.8317	0.003194
11	0.324313	2.4485	0.008723
12	0.278324	2.1013	0.020024
13	0.232326	1.754	0.042401
14	0.202091	1.5258	0.066301
15	0.181149	1.3676	0.088396
16	0.164527	1.2421	0.109634
17	0.142137	1.0731	0.143872
18	0.114059	0.8611	0.196389
19	0.083717	0.632	0.264941
20	0.035129	0.2652	0.3959
21	-0.002454	-0.0185	0.492642
22	-0.035396	-0.2672	0.395128
23	-0.068182	-0.5148	0.304356
24	-0.10354	-0.7817	0.21881
25	-0.144758	-1.0929	0.139517
26	-0.178649	-1.3488	0.091373
27	-0.209032	-1.5782	0.060032
28	-0.235613	-1.7788	0.040299
29	-0.251203	-1.8965	0.03148
30	-0.255327	-1.9277	0.029441
31	-0.265808	-2.0068	0.024761
32	-0.281268	-2.1235	0.019031
33	-0.293232	-2.2139	0.015428
34	-0.321131	-2.4245	0.009262
35	-0.35194	-2.6571	0.005104
36	-0.365659	-2.7607	0.003873
37	-0.372686	-2.8137	0.003354
38	-0.378215	-2.8555	0.002992
39	-0.393068	-2.9676	0.002191
40	-0.402617	-3.0397	0.001786
41	-0.412029	-3.1108	0.001457
42	-0.416119	-3.1416	0.001332
43	-0.413128	-3.119	0.001422
44	-0.400778	-3.0258	0.001858
45	-0.376793	-2.8447	0.003082
46	-0.34271	-2.5874	0.006123
47	-0.304742	-2.3008	0.012542
48	-0.261594	-1.975	0.02656

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.951752	7.1856	0
2	-0.266028	-2.0085	0.02467
3	-0.00699	-0.0528	0.479047
4	-0.018351	-0.1385	0.445148
5	0.04542	0.3429	0.366463
6	-0.01077	-0.0813	0.467738
7	-0.053298	-0.4024	0.34445
8	-0.131911	-0.9959	0.161752
9	0.027099	0.2046	0.419308
10	0.01738	0.1312	0.448033
11	0.001804	0.0136	0.494589
12	-0.027477	-0.2074	0.418201
13	-0.056573	-0.4271	0.335453
14	0.163715	1.236	0.110761
15	0.015731	0.1188	0.452939
16	-0.010739	-0.0811	0.467833
17	-0.123576	-0.933	0.177384
18	-0.036575	-0.2761	0.391722
19	-0.004374	-0.033	0.486885
20	-0.225457	-1.7022	0.047087
21	0.142786	1.078	0.142784
22	-0.087058	-0.6573	0.256825
23	-0.019255	-0.1454	0.442465
24	-0.065602	-0.4953	0.311152
25	-0.07713	-0.5823	0.281323
26	0.085222	0.6434	0.261269
27	-0.007105	-0.0536	0.478704
28	-0.044599	-0.3367	0.368784
29	0.078889	0.5956	0.2769
30	0.040484	0.3057	0.380492
31	-0.164953	-1.2454	0.109045
32	-0.005985	-0.0452	0.482058
33	-0.078026	-0.5891	0.279067
34	-0.211707	-1.5983	0.057747
35	0.018333	0.1384	0.4452
36	0.186836	1.4106	0.081901
37	-0.096378	-0.7276	0.234907
38	-0.079286	-0.5986	0.275906
39	-0.069175	-0.5223	0.301756
40	0.068027	0.5136	0.30476
41	0.023242	0.1755	0.430664
42	-0.000454	-0.0034	0.498637
43	-0.002135	-0.0161	0.493598
44	0.087019	0.657	0.256919
45	0.010079	0.0761	0.469804
46	0.103298	0.7799	0.219343
47	-0.046725	-0.3528	0.362782
48	-0.022761	-0.1718	0.432085

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/10/t1292007582iosz5cmj8xy676z/1dzsq1292007698.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t1292007582iosz5cmj8xy676z/1dzsq1292007698.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t1292007582iosz5cmj8xy676z/2o9st1292007698.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t1292007582iosz5cmj8xy676z/2o9st1292007698.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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