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Uitvoer Amerika (Partial) autocorrelation D=1 en 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: Thu, 04 Dec 2008 11:20:00 -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/04/t12284148586uodbdqrr36bugq.htm/, Retrieved Thu, 04 Dec 2008 18:21:01 +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/04/t12284148586uodbdqrr36bugq.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 «
1190.8 728.8 995.6 1260.3 994 957.3 975.6 884.9 908.4 1022.8 958.6 825.1 1116.6 724.2 1004.5 1058.9 854.7 943.4 792.4 873.2 1101.4 987.1 1038.8 1060.7 1047.7 840 1044 1097.4 987.5 934 977 881.1 1083.3 1074.7 1182.2 1117.5 1117.4 936.2 1246.3 1175.1 1177.7 1035.8 1091.6 998.7 1247.9 1034.7 1287.7 994.0 1122.8 1017.3 1106.0 1191.8 1030.1 989.4 979.6 1088.0 1389.2 1043.9 1182.1 1109.6 1463.3 1276.2 1082.4 1360.4 1130.2 1019.6 1077.0 958.8 959.6 907.2 880.8 759.6 1137.2
 
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
1-0.439447-3.40390.000595
2-0.131401-1.01780.156424
30.2436221.88710.031995
4-0.121025-0.93750.17614
50.0352260.27290.392949
60.1290120.99930.160826
7-0.140088-1.08510.141105
8-0.007918-0.06130.47565
9-0.063115-0.48890.313353
100.0785660.60860.272554
110.0263760.20430.419401
12-0.109145-0.84540.200614
130.0011930.00920.496328
140.0026470.02050.491854
150.0149090.11550.454224
16-0.014543-0.11260.455343
170.0028470.02210.491238
180.1000120.77470.220784
19-0.117596-0.91090.182997
20-0.025324-0.19620.422574
210.2245581.73940.043545
22-0.242824-1.88090.03242
230.2460241.90570.030742
24-0.148391-1.14940.12747
25-0.074144-0.57430.283949
260.1911181.48040.072
27-0.067237-0.52080.302206
28-0.090601-0.70180.242761
290.0829240.64230.261554
30-0.042063-0.32580.372848
31-0.011338-0.08780.465153
320.0068930.05340.478798
330.0480980.37260.355391
34-0.085384-0.66140.255451
350.0011940.00920.496326
360.0776950.60180.274779
37-0.018481-0.14310.443326
38-0.019699-0.15260.439617
390.007710.05970.476288
40-0.015447-0.11970.452579
410.0820380.63550.263771
42-0.110446-0.85550.197836
430.0526590.40790.342401
440.1167570.90440.184702
45-0.257693-1.99610.025235
460.1136610.88040.191074
470.1083270.83910.202372
48-0.201178-1.55830.062208
490.0600190.46490.321842
500.060590.46930.320267
51-0.120499-0.93340.177183
520.0619520.47990.316528
530.0532170.41220.340825
54-0.075172-0.58230.281279
550.0124040.09610.461888
560.0217870.16880.433276
57-0.013321-0.10320.459082
58-0.002016-0.01560.493797
590.00150.01160.495385
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.439447-3.40390.000595
2-0.40218-3.11530.001409
3-0.02082-0.16130.436212
4-0.048147-0.37290.355251
50.0558110.43230.333533
60.1902441.47360.072905
70.0676880.52430.300998
8-0.032925-0.2550.399784
9-0.257813-1.9970.025183
10-0.136942-1.06070.146528
11-0.029191-0.22610.410942
12-0.036516-0.28280.389133
13-0.045318-0.3510.363396
14-0.056516-0.43780.331562
150.0107650.08340.466912
16-0.060762-0.47070.319796
17-0.04699-0.3640.358574
180.1593491.23430.11095
190.0779980.60420.274004
20-0.073266-0.56750.286241
210.091630.70980.240299
22-0.145731-1.12880.131732
230.2180541.6890.048202
24-0.083433-0.64630.260284
25-0.057782-0.44760.328036
260.0284330.22020.413217
270.0499050.38660.350222
28-0.05068-0.39260.348017
29-0.09903-0.76710.223021
300.0858250.66480.254364
310.0208140.16120.43623
32-0.042191-0.32680.372475
330.0377170.29220.385587
34-0.01796-0.13910.444913
350.0137120.10620.457884
36-0.018396-0.14250.443582
370.0389420.30160.381982
380.0822680.63720.263194
39-0.02891-0.22390.411783
40-0.049273-0.38170.352028
410.0335960.26020.397788
42-0.086444-0.66960.252844
430.0492860.38180.351991
440.0214610.16620.434266
45-0.04163-0.32250.37411
46-0.109856-0.85090.199093
470.0101160.07840.468903
48-0.089051-0.68980.246494
49-0.107713-0.83430.203699
500.0299450.2320.408681
51-0.020838-0.16140.436157
520.0043580.03380.486593
530.0485180.37580.354188
54-0.033649-0.26060.397629
550.0237410.18390.427356
56-0.057922-0.44870.327645
57-0.042491-0.32910.3716
58-0.103729-0.80350.212434
59-0.109644-0.84930.199545
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t12284148586uodbdqrr36bugq/1ekuz1228414798.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t12284148586uodbdqrr36bugq/1ekuz1228414798.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t12284148586uodbdqrr36bugq/2ys0h1228414798.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/04/t12284148586uodbdqrr36bugq/2ys0h1228414798.ps (open in new window)


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