*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, 30 Nov 2009 10:42:15 -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/Nov/30/t1259602999e26b84iprunmxsl.htm/, Retrieved Mon, 30 Nov 2009 18:43:22 +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/Nov/30/t1259602999e26b84iprunmxsl.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 «

1.4 1.2 1 1.7 2.4 2 2.1 2 1.8 2.7 2.3 1.9 2 2.3 2.8 2.4 2.3 2.7 2.7 2.9 3 2.2 2.3 2.8 2.8 2.8 2.2 2.6 2.8 2.5 2.4 2.3 1.9 1.7 2 2.1 1.7 1.8 1.8 1.8 1.3 1.3 1.3 1.2 1.4 2.2 2.9 3.1 3.5 3.6 4.4 4.1 5.1 5.8 5.9 5.4 5.5 4.8 3.2 2.7 2.1 1.9 0.6 0.7 -0.2 -1 -1.7 -0.7 -1

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 8 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Autocorrelation Function Time lag k ACF(k) T-STAT P-value 1 0.173982 1.4347 0.07798 2 0.134929 1.1127 0.134887 3 0.182436 1.5044 0.068553 4 0.276022 2.2761 0.012996 5 0.037263 0.3073 0.379785 6 0.062281 0.5136 0.304605 7 0.060478 0.4987 0.309796 8 -0.025453 -0.2099 0.417191 9 -0.180185 -1.4858 0.070972 10 -0.087832 -0.7243 0.23569 11 0.052599 0.4337 0.332924 12 -0.443573 -3.6578 0.000249 13 -0.22298 -1.8387 0.03516 14 -0.079751 -0.6576 0.256494 15 0.006305 0.052 0.479344 16 -0.172815 -1.4251 0.079355 17 -0.119611 -0.9863 0.163732 18 -0.039219 -0.3234 0.373689 19 0.005156 0.0425 0.483104 20 -0.102364 -0.8441 0.200782 21 0.006548 0.054 0.478549 22 0.086307 0.7117 0.239541 23 -0.052099 -0.4296 0.334415 24 -0.033945 -0.2799 0.390195 25 0.106052 0.8745 0.192454 26 0.051307 0.4231 0.336782 27 -0.062277 -0.5135 0.304616 28 0.036373 0.2999 0.382568 29 0.05546 0.4573 0.324443 30 0.049359 0.407 0.342633 31 -0.043401 -0.3579 0.360765 32 0.053416 0.4405 0.330493 33 0.09306 0.7674 0.222751 34 -0.000133 -0.0011 0.499563 35 -0.066706 -0.5501 0.292036 36 0.097547 0.8044 0.211988 37 -0.003877 -0.032 0.487296 38 -0.020173 -0.1664 0.434187 39 0.028101 0.2317 0.408724 40 0.031895 0.263 0.396668 41 -0.010489 -0.0865 0.465663 42 -0.03175 -0.2618 0.397127 43 0.054539 0.4497 0.327163 44 0.054069 0.4459 0.328556 45 -0.057483 -0.474 0.318503 46 -0.060519 -0.4991 0.309677 47 0.053791 0.4436 0.329381 48 -0.037804 -0.3117 0.378096 49 -0.01222 -0.1008 0.460016 50 0.057077 0.4707 0.319691 51 -0.063604 -0.5245 0.300822 52 -0.060242 -0.4968 0.310476 53 -0.020165 -0.1663 0.434213 54 -0.024734 -0.204 0.419498 55 -0.079179 -0.6529 0.258003 56 -0.070986 -0.5854 0.280118 57 -0.025112 -0.2071 0.418284 58 0.009968 0.0822 0.467366 59 -0.049475 -0.408 0.342285 60 -0.007665 -0.0632 0.474893 Partial Autocorrelation Function Time lag k PACF(k) T-STAT P-value 1 0.173982 1.4347 0.07798 2 0.107926 0.89 0.188306 3 0.148907 1.2279 0.111856 4 0.227584 1.8767 0.032425 5 -0.066566 -0.5489 0.292429 6 -0.005312 -0.0438 0.482596 7 -0.01873 -0.1544 0.438857 8 -0.104074 -0.8582 0.196894 9 -0.190375 -1.5699 0.060544 10 -0.066537 -0.5487 0.292512 11 0.124284 1.0249 0.154528 12 -0.439521 -3.6244 0.000277 13 -0.035066 -0.2892 0.386667 14 0.061274 0.5053 0.307498 15 0.135428 1.1168 0.134013 16 0.078089 0.6439 0.260892 17 -0.093751 -0.7731 0.221074 18 0.007919 0.0653 0.474062 19 0.030559 0.252 0.400901 20 -0.066232 -0.5462 0.293371 21 -0.116395 -0.9598 0.170274 22 0.010617 0.0876 0.465245 23 0.055777 0.4599 0.323511 24 -0.216288 -1.7836 0.039479 25 0.030983 0.2555 0.399558 26 -0.014929 -0.1231 0.451194 27 0.045344 0.3739 0.354816 28 0.121925 1.0054 0.15913 29 -0.112614 -0.9286 0.17818 30 0.037118 0.3061 0.380237 31 0.017705 0.146 0.442176 32 0.004551 0.0375 0.485088 33 0.000211 0.0017 0.499308 34 -0.002902 -0.0239 0.49049 35 -0.053032 -0.4373 0.331636 36 -0.044999 -0.3711 0.355869 37 -0.00803 -0.0662 0.473698 38 -0.022096 -0.1822 0.42798 39 0.073912 0.6095 0.272114 40 0.056116 0.4627 0.322512 41 -0.069236 -0.5709 0.284964 42 0.047121 0.3886 0.349403 43 0.063551 0.5241 0.300972 44 0.019806 0.1633 0.435373 45 -0.025082 -0.2068 0.41838 46 -0.049925 -0.4117 0.340931 47 -0.062638 -0.5165 0.303582 48 -0.038364 -0.3164 0.376349 49 0.034023 0.2806 0.389948 50 0.097805 0.8065 0.211376 51 -0.098709 -0.814 0.209251 52 -0.00301 -0.0248 0.490136 53 -0.010355 -0.0854 0.466101 54 -0.052409 -0.4322 0.33349 55 -0.030781 -0.2538 0.400198 56 0.014431 0.119 0.452813 57 0.042219 0.3481 0.364402 58 -0.03811 -0.3143 0.377143 59 -0.024213 -0.1997 0.42117 60 0.002199 0.0181 0.492793

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/30/t1259602999e26b84iprunmxsl/1ncad1259602927.png (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/30/t1259602999e26b84iprunmxsl/1ncad1259602927.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/30/t1259602999e26b84iprunmxsl/2xf4b1259602927.png (open in new window) http://www.freestatistics.org/blog/date/2009/Nov/30/t1259602999e26b84iprunmxsl/2xf4b1259602927.ps (open in new window)

Parameters (Session):

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

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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')

Copyright

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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