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ACF Invoer

*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: Mon, 22 Dec 2008 09:29:05 -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/22/t12299633738mi2sbs357d2whl.htm/, Retrieved Mon, 22 Dec 2008 17:29:35 +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/2008/Dec/22/t12299633738mi2sbs357d2whl.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},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
14532,2 15167 16071,1 14827,5 15082 14772,7 16083 14272,5 15223,3 14897,3 13062,6 12603,8 13629,8 14421,1 13978,3 12927,9 13429,9 13470,1 14785,8 14292 14308,8 14013 13240,9 12153,4 14289,7 15669,2 14169,5 14569,8 14469,1 14264,9 15320,9 14433,5 13691,5 14194,1 13519,2 11857,9 14616 15643,4 14077,2 14887,5 14159,9 14643 17192,5 15386,1 14287,1 17526,6 14497 14398,3 16629,6 16670,7 16614,8 16869,2 15663,9 16359,9 18447,7 16889 16505 18320,9 15052,1 15699,8 18135,3 16768,7 18883 19021 18101,9 17776,1 21489,9 17065,3 18690 18953,1 16398,9 16895,7 18553 19270 19422,1 17579,4 18637,3 18076,7 20438,6 18075,2 19563 19899,2 19227,5 17789,6 19220,8 22058,6 21230,8 19504,4 23913,1 23165,7 23574,3 25002 22603,9 23408,6
 
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
10.8205437.95550
20.7689547.45530
30.7663737.43030
40.6773126.56680
50.6357586.16390
60.6215216.02590
70.5604345.43360
80.5361035.19771e-06
90.5174435.01681e-06
100.4630694.48961e-05
110.4902564.75324e-06
120.5401875.23730
130.4252184.12264e-05
140.391183.79260.000132
150.4022253.89979e-05
160.3462433.3570.000569
170.3503383.39670.000501
180.3388553.28530.000716
190.3042892.95020.002004
200.2873992.78640.003224
210.2645822.56520.005947
220.2294662.22480.014245
230.2646582.5660.005935
240.278922.70420.004064
250.2165992.10.019203
260.1755091.70160.046066
270.1613851.56470.060508
280.1080681.04780.148719
290.0975360.94560.173376
300.0564070.54690.292875
310.0285250.27660.391362
32-0.002269-0.0220.491249
33-0.026687-0.25870.3982
34-0.05476-0.53090.298365
35-0.03191-0.30940.378858
36-0.018125-0.17570.430442
37-0.070436-0.68290.248175
38-0.109145-1.05820.146337
39-0.120643-1.16970.122544
40-0.147161-1.42680.078478
41-0.164301-1.5930.057263
42-0.184566-1.78940.038382
43-0.187767-1.82050.035935
44-0.21214-2.05680.021239
45-0.246382-2.38880.009452
46-0.247375-2.39840.009221
47-0.249352-2.41760.008777
48-0.22806-2.21110.014726
49-0.271961-2.63680.004897
50-0.304458-2.95180.001994
51-0.302454-2.93240.002112
52-0.319582-3.09850.001283
53-0.334188-3.24010.000826
54-0.327118-3.17150.001024
55-0.332561-3.22430.000869
56-0.335011-3.24810.000806
57-0.342816-3.32370.000634
58-0.334281-3.2410.000824
59-0.317124-3.07460.00138
60-0.280591-2.72040.003884


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8205437.95550
20.2928092.83890.002774
30.2674982.59350.00551
4-0.11778-1.14190.128195
50.0075590.07330.470868
60.0634720.61540.269893
7-0.036863-0.35740.360796
80.0369760.35850.360387
90.0164120.15910.436956
10-0.053221-0.5160.303534
110.1886831.82930.035259
120.2590152.51120.006869
13-0.352049-3.41320.000474
14-0.189924-1.84140.03436
150.0704550.68310.248115
160.1161811.12640.131429
170.124441.20650.115328
18-0.102978-0.99840.160321
19-0.054151-0.5250.300403
20-0.041068-0.39820.345705
210.0607290.58880.278709
220.0222020.21530.415018
230.0175690.17030.432554
24-0.019238-0.18650.42622
250.0081680.07920.468525
26-0.14602-1.41570.080081
27-0.104446-1.01260.156915
28-0.068136-0.66060.25524
290.0308420.2990.382792
30-0.064838-0.62860.26556
310.0315080.30550.380336
32-0.044398-0.43050.333926
330.0702040.68060.248883
34-0.038863-0.37680.353588
35-0.020195-0.19580.422597
360.0131280.12730.449494
37-0.074892-0.72610.23479
38-0.079657-0.77230.220935
39-0.019466-0.18870.425354
400.022270.21590.414761
41-0.029992-0.29080.385928
42-0.035675-0.34590.365103
430.0561450.54430.293746
44-0.021169-0.20520.418915
45-0.081035-0.78570.21702
460.0129760.12580.450077
47-0.075411-0.73110.233256
480.0463580.44950.327068
49-0.041735-0.40460.343332
50-0.043667-0.42340.336496
51-0.010944-0.10610.457862
52-0.01152-0.11170.455654
530.0328330.31830.375472
540.0190640.18480.42688
55-0.047112-0.45680.324446
560.0632390.61310.270637
570.0632030.61280.270751
58-0.032093-0.31120.378186
59-0.041508-0.40240.34414
60-0.011221-0.10880.456798
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t12299633738mi2sbs357d2whl/110ry1229963342.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t12299633738mi2sbs357d2whl/110ry1229963342.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t12299633738mi2sbs357d2whl/2nh7v1229963342.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t12299633738mi2sbs357d2whl/2nh7v1229963342.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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