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bel 20 - autocorr with d=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: Sun, 20 Dec 2009 02:46:06 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/20/t1261302558aiadii6s2qvjamq.htm/, Retrieved Sun, 20 Dec 2009 10:49:21 +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/2009/Dec/20/t1261302558aiadii6s2qvjamq.htm/},
    year = {2009},
}
@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 = {2009},
    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 «

2921.44 2981.85 3080.58 3106.22 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.1 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.4 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.4 3857.62 3801.06 3504.37 3032.6 3047.03 2962.34 2197.82 2014.45 1862.83 1905.41 1810.99 1670.07 1864.44 2052.02 2029.6 2070.83 2293.41 2443.27 2513.17 2466.92

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	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.28833	2.2147	0.015327
2	0.075299	0.5784	0.282603
3	0.21863	1.6793	0.049188
4	0.232184	1.7834	0.039829
5	0.255974	1.9662	0.026995
6	-0.027258	-0.2094	0.417438
7	-0.045959	-0.353	0.362667
8	0.143323	1.1009	0.137709
9	0.027587	0.2119	0.416459
10	-0.16052	-1.233	0.111236
11	0.123461	0.9483	0.173417
12	-0.011932	-0.0917	0.463643
13	-0.041828	-0.3213	0.374565
14	0.053236	0.4089	0.342041
15	-0.057868	-0.4445	0.329155
16	0.04131	0.3173	0.376064
17	-0.126301	-0.9701	0.167969
18	-0.174561	-1.3408	0.092558
19	0.017571	0.135	0.44655
20	-0.096099	-0.7382	0.231674
21	-0.172927	-1.3283	0.0946
22	-0.180754	-1.3884	0.085118
23	-0.162856	-1.2509	0.10795
24	-0.119038	-0.9143	0.182128
25	-0.070054	-0.5381	0.296268
26	-0.12236	-0.9399	0.17556
27	-0.029344	-0.2254	0.411224
28	0.052211	0.401	0.344921
29	-0.03703	-0.2844	0.388538
30	-0.040484	-0.311	0.378461
31	-0.081034	-0.6224	0.268028
32	-0.020416	-0.1568	0.437961
33	-0.041045	-0.3153	0.376835
34	-0.089893	-0.6905	0.2463
35	-0.114029	-0.8759	0.192326
36	-0.044053	-0.3384	0.368141
37	-0.006936	-0.0533	0.478847
38	-0.031991	-0.2457	0.403373
39	-0.053269	-0.4092	0.34195
40	-0.046688	-0.3586	0.360581
41	0.011452	0.088	0.465102
42	0.014646	0.1125	0.455405
43	0.023407	0.1798	0.428967
44	-0.006825	-0.0524	0.479184
45	0.003889	0.0299	0.488136
46	0.012314	0.0946	0.462481
47	0.001708	0.0131	0.494789
48	0.007335	0.0563	0.47763
49	0.014267	0.1096	0.456553
50	0.023042	0.177	0.430061
51	0.016546	0.1271	0.44965
52	0.005606	0.0431	0.482899
53	0.004948	0.038	0.484906
54	0.018955	0.1456	0.442367
55	0.017709	0.136	0.446132
56	0.009158	0.0703	0.47208
57	0.000612	0.0047	0.498133
58	-0.001358	-0.0104	0.495857
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.28833	2.2147	0.015327
2	-0.008545	-0.0656	0.473944
3	0.217275	1.6689	0.050216
4	0.127021	0.9757	0.166606
5	0.183771	1.4116	0.081664
6	-0.201929	-1.551	0.06312
7	-0.054693	-0.4201	0.337968
8	0.072196	0.5545	0.290651
9	-0.062619	-0.481	0.316154
10	-0.172829	-1.3275	0.094725
11	0.303653	2.3324	0.011556
12	-0.17579	-1.3503	0.091044
13	0.014487	0.1113	0.455887
14	0.109795	0.8434	0.201218
15	-0.055905	-0.4294	0.334592
16	-0.088075	-0.6765	0.250678
17	-0.098264	-0.7548	0.226691
18	-0.061399	-0.4716	0.31947
19	-0.007782	-0.0598	0.476269
20	-0.087373	-0.6711	0.252381
21	0.056539	0.4343	0.332833
22	-0.204513	-1.5709	0.060778
23	-0.003873	-0.0297	0.488184
24	-0.044682	-0.3432	0.366331
25	0.050161	0.3853	0.350703
26	0.011482	0.0882	0.465009
27	0.054821	0.4211	0.337611
28	0.108125	0.8305	0.204796
29	-0.020348	-0.1563	0.438167
30	-0.161084	-1.2373	0.110436
31	0.009656	0.0742	0.470564
32	-0.082673	-0.635	0.263934
33	-0.085754	-0.6587	0.256328
34	0.007426	0.057	0.477352
35	-0.039184	-0.301	0.382246
36	0.027114	0.2083	0.41787
37	0.037237	0.286	0.387931
38	0.070512	0.5416	0.295063
39	-0.137083	-1.053	0.148328
40	-0.066836	-0.5134	0.304801
41	0.01208	0.0928	0.463193
42	-0.048672	-0.3739	0.354926
43	0.018543	0.1424	0.443612
44	0.016206	0.1245	0.450679
45	-0.021751	-0.1671	0.433943
46	-0.008599	-0.0661	0.47378
47	-0.048054	-0.3691	0.356685
48	0.011635	0.0894	0.464546
49	0.020766	0.1595	0.436907
50	0.041888	0.3217	0.374391
51	0.016278	0.125	0.450462
52	-0.034768	-0.2671	0.395177
53	-0.049124	-0.3773	0.353642
54	-0.038855	-0.2985	0.383204
55	-0.038756	-0.2977	0.383491
56	-0.054491	-0.4186	0.338532
57	-0.089944	-0.6909	0.246176
58	0.06285	0.4828	0.315526
59	NA	NA	NA
60	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/20/t1261302558aiadii6s2qvjamq/1zi031261302364.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/20/t1261302558aiadii6s2qvjamq/1zi031261302364.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/20/t1261302558aiadii6s2qvjamq/2r8dx1261302364.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/20/t1261302558aiadii6s2qvjamq/2r8dx1261302364.ps (open in new window)

Parameters (Session):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 60 ; 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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