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*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, 17 Dec 2009 20:26:45 +0100
 
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/17/t1261078052s553syl4tp9ln3a.htm/, Retrieved Thu, 17 Dec 2009 20:27:34 +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/17/t1261078052s553syl4tp9ln3a.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 «
277 260.6 291.6 275.4 275.3 231.7 238.8 274.2 277.8 299.1 286.6 232.3 294.1 267.5 309.7 280.7 287.3 235.7 256.4 289 290.8 321.9 291.8 241.4 295.5 258.2 306.1 281.5 283.1 237.4 274.8 299.3 300.4 340.9 318.8 265.7 322.7 281.6 323.5 312.6 310.8 262.8 273.8 320 310.3 342.2 320.1 265.6 327 300.7 346.4 317.3 326.2 270.7 278.2 324.6 321.8 343.5 354 278.2 330.2 307.3 375.9 335.3 339.3 280.3 293.7 341.2 345.1 368.7 369.4 288.4 341 319.1 374.2 344.5 337.3 281 282.2 321 325.4 366.3 380.3 300.7 359.3 327.6 383.6 352.4 329.4 294.5 333.5 334.3 358 396.1 387 307.2 363.9 344.7 397.6 376.8 337.1 299.3 323.1 329.1 347 462 436.5 360.4 415.5 382.1 432.2 424.3 386.7 354.5 375.8 368 402.4 426.5 433.3 338.5 416.8 381.1 445.7 412.4 394 348.2 380.1 373.7 393.6 434.2 430.7 344.5 411.9 370.5 437.3 411.3 385.5 341.3 384.2 373.2 415.8 448.6 454.3 350.3 419.1 398 456.1 430.1 399.8 362.7 384. etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.477054-6.27470
20.1343821.76750.039452
3-0.110352-1.45150.074232
40.0536870.70610.240527
5-0.119803-1.57580.058453
60.0426210.56060.287901
70.027920.36720.356948
80.0406550.53470.296761
90.0205490.27030.393634
10-0.135087-1.77680.03868
110.2596583.41530.000397
12-0.460579-6.0580
130.2423013.1870.000853
14-0.20139-2.64890.004412
150.2869653.77440.00011
16-0.077162-1.01490.155784
17-0.033297-0.4380.330984
180.0165440.21760.413998
190.0235340.30950.378641
20-0.085647-1.12650.130754
210.0077690.10220.459365
220.0983241.29330.098824
23-0.103989-1.36780.08658
240.1455691.91470.028593
25-0.13307-1.75030.040923
260.1631122.14540.016658
27-0.193419-2.5440.005917
28-0.027551-0.36240.358756
290.1444861.90040.029521
30-0.097736-1.28550.100165
310.0443560.58340.280188
320.0317550.41770.338353
33-0.013383-0.1760.430239
34-0.022859-0.30070.382019
350.0382530.50310.307754
36-0.090296-1.18770.118298
370.121231.59450.056321
38-0.120568-1.58580.057303
390.0418920.5510.291171
400.0907681.19390.117082
41-0.078207-1.02870.152538
420.0319390.42010.33747
43-0.0731-0.96150.168825
440.0932041.22590.110949
45-0.078623-1.03410.151262
46-0.001912-0.02520.489981
470.0730190.96040.169094
48-0.028117-0.36980.355984
49-0.045277-0.59550.276135
500.068150.89640.185651
51-0.011904-0.15660.437882
52-0.099604-1.31010.095951
530.1116471.46850.071893
54-0.138021-1.81540.035598
550.1970122.59130.005189
56-0.10282-1.35240.089008
570.0224490.29530.384068
58-0.006155-0.0810.467785
59-0.015521-0.20410.419239
60-0.018839-0.24780.402295


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.477054-6.27470
2-0.120657-1.5870.05717
3-0.126212-1.66010.049357
4-0.055962-0.73610.231346
5-0.157262-2.06850.020042
6-0.123127-1.61950.053582
7-0.016438-0.21620.41454
80.0497950.65490.256686
90.0843931.110.134267
10-0.126988-1.67030.048337
110.198532.61120.004907
12-0.337082-4.43368e-06
13-0.163686-2.1530.016354
14-0.269547-3.54530.000252
150.050260.66110.254725
160.1478891.94520.026687
17-0.130994-1.7230.043342
18-0.042484-0.55880.288515
19-0.008128-0.10690.457495
200.0123630.16260.43551
21-0.005791-0.07620.469688
22-0.035621-0.46850.32
230.0210180.27640.391269
24-0.095174-1.25180.106164
25-0.057949-0.76220.223487
26-0.058024-0.76320.223196
270.0033870.04450.48226
28-0.126251-1.66060.049305
290.0658850.86660.193686
30-0.112169-1.47530.070968
31-0.055442-0.72920.233424
320.0479190.63030.264675
33-0.026251-0.34530.365151
340.0236540.31110.378042
350.002450.03220.487167
36-0.019965-0.26260.396587
37-0.007379-0.09710.461396
38-0.058755-0.77280.220346
39-0.100235-1.31840.094558
40-0.032424-0.42650.335148
410.0476520.62680.265818
42-0.048041-0.63190.264149
43-0.027721-0.36460.357924
440.0231060.30390.380782
45-0.019743-0.25970.397708
46-0.040554-0.53340.297221
470.0731890.96260.168534
48-0.062777-0.82570.205055
49-0.011607-0.15270.43942
50-0.022804-0.29990.382291
51-0.031876-0.41930.337772
52-0.108425-1.42610.077819
530.0276080.36310.358477
54-0.10184-1.33950.091083
550.0278910.36680.357091
560.0657580.86490.194143
57-0.015837-0.20830.417618
58-0.042078-0.55340.290336
59-0.005028-0.06610.473674
60-0.03255-0.42810.334545
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/17/t1261078052s553syl4tp9ln3a/1jmp01261078000.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/17/t1261078052s553syl4tp9ln3a/1jmp01261078000.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/17/t1261078052s553syl4tp9ln3a/26c8m1261078000.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/17/t1261078052s553syl4tp9ln3a/26c8m1261078000.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; 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')
 





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