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Paper

*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: Thu, 11 Dec 2008 05:41:13 -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/11/t1228999368jiz3c1588hmitvw.htm/, Retrieved Thu, 11 Dec 2008 12:42:50 +0000
 
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/11/t1228999368jiz3c1588hmitvw.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},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:
2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply] 
test

Post a new message
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
98,6 98 106,8 96,6 100,1 107,7 91,5 97,8 107,4 117,5 105,6 97,4 99,5 98 104,3 100,6 101,1 103,9 96,9 95,5 108,4 117 103,8 100,8 110,6 104 112,6 107,3 98,9 109,8 104,9 102,2 123,9 124,9 112,7 121,9 100,6 104,3 120,4 107,5 102,9 125,6 107,5 108,8 128,4 121,1 119,5 128,7 108,7 105,5 119,8 111,3 110,6 120,1 97,5 107,7 127,3 117,2 119,8 116,2 111 112,4 130,6 109,1 118,8 123,9 101,6 112,8 128 129,6 125,8 119,5 115,7 113,6 129,7 112 116,8 127 112,1 114,2 121,1 131,6 125 120,4
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.422933.87620.000105
20.2506842.29760.012037
30.4928254.51681e-05
40.2122061.94490.027567
50.2957872.71090.004067
60.542724.97412e-06
70.2206652.02240.023157
80.195081.78790.038696
90.4082443.74160.000167
100.1174091.07610.142488
110.3122042.86140.002661
120.6517965.97380
130.225922.07060.020734
140.1578661.44690.075828
150.2607482.38980.009548
160.0145250.13310.447205
170.1583561.45140.075202
180.291322.670.004552
190.0139420.12780.449315
200.0306530.28090.389724
210.1536871.40860.081327
22-0.068561-0.62840.265733
230.1422341.30360.097967
240.3064552.80870.003092
250.0358160.32830.371765
260.0123340.1130.455131
270.055010.50420.307728
28-0.145505-1.33360.092973
29-0.02436-0.22330.411937
300.0913620.83730.202388
31-0.10915-1.00040.160002
32-0.078306-0.71770.237472
33-0.033026-0.30270.381439
34-0.152685-1.39940.082691
350.0283960.26030.397651
360.1858281.70310.046119
37-0.032001-0.29330.385011
38-0.076401-0.70020.242859
39-0.054518-0.49970.309307
40-0.190311-1.74420.042388
41-0.132112-1.21080.114679
42-0.064471-0.59090.278092
43-0.160187-1.46810.072901
44-0.146688-1.34440.091217
45-0.164047-1.50350.068228
46-0.220357-2.01960.023306
47-0.093424-0.85620.197149
480.0357560.32770.371973
49-0.110176-1.00980.157749
50-0.158462-1.45230.075068
51-0.167161-1.53210.064634
52-0.218956-2.00680.023996
53-0.151837-1.39160.083858
54-0.159563-1.46240.073679
55-0.205055-1.87940.031831
56-0.200724-1.83970.034675
57-0.196367-1.79970.037746
58-0.251729-2.30710.011754
59-0.179189-1.64230.052133
60-0.081439-0.74640.228755


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.422933.87620.000105
20.0874580.80160.212533
30.4406784.03895.9e-05
4-0.189865-1.74010.042748
50.3255482.98370.001864
60.2340332.14490.017423
7-0.107191-0.98240.164356
80.0039470.03620.485614
90.1218491.11680.13364
10-0.163428-1.49780.068961
110.3443773.15630.00111
120.3375653.09380.001342
13-0.173057-1.58610.058238
14-0.158603-1.45360.074888
15-0.245671-2.25160.013478
16-0.059461-0.5450.293609
17-0.05125-0.46970.319887
18-0.112015-1.02660.153769
190.0308930.28310.388884
20-0.105799-0.96970.167499
210.0344780.3160.376394
22-0.007344-0.06730.473248
230.0786090.72050.236619
24-0.05204-0.4770.317317
250.0899940.82480.205909
26-0.112327-1.02950.1531
270.1230461.12770.131322
28-0.164652-1.50910.067518
29-0.015885-0.14560.442297
300.0012260.01120.495531
310.0675740.61930.268689
32-0.011577-0.10610.457876
33-0.013642-0.1250.4504
340.0242260.2220.412414
350.054850.50270.308243
360.1709881.56710.060422
37-0.073917-0.67750.249989
38-0.07159-0.65610.256766
39-0.12235-1.12140.132666
400.0096190.08820.464979
41-0.144062-1.32030.095153
42-0.155256-1.42290.079227
430.0746810.68450.247784
44-0.051991-0.47650.317475
45-0.027471-0.25180.400914
46-0.034725-0.31830.375538
47-0.008092-0.07420.470526
48-0.050816-0.46570.321304
49-0.009995-0.09160.463614
500.0124710.11430.454636
510.0044530.04080.483771
520.071530.65560.256943
530.0875240.80220.212358
54-0.02834-0.25970.397849
55-0.047633-0.43660.331772
56-0.001072-0.00980.496091
570.0375340.3440.365852
58-0.078596-0.72030.236657
59-0.107647-0.98660.163337
60-0.04882-0.44740.327854
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1228999368jiz3c1588hmitvw/17uzf1228999272.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1228999368jiz3c1588hmitvw/17uzf1228999272.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1228999368jiz3c1588hmitvw/2eui61228999272.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1228999368jiz3c1588hmitvw/2eui61228999272.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; 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')
 




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