Re: [R] Cross-correlation between two time series data
'ccf' provides a plot with red, dashed lines indicating an approximate 95% threshold for the correlation. Beyond that, with any particular model fit, you can get confidence intervals and anova tests for any particular parameter estimated. If neither of these are adequate, I suppose one might be able to try Markov Chain Monte Carlo, but I've never used that, so I can't comment further on that. If you would like more help from this listserve, please provide more detail of your application including commented, minimal, self-contained, reproducible code, explaining something you've tried and why it is not adequate (as suggested in the posting guide www.R-project.org/posting-guide.html). Hope this helps. Spencer Graves Juni Joshi wrote: Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not provide the confidence intervals of cross correlation. Is there any function that calculates the confidence interval of correlation between two time series data or performs the test of no correlation between two time series data. Thanks. Jun __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Cross-correlation between two time series data
Jun, If your interest is to estimate the correlation and either a confidence interval or a test for no correlation, then you might try to proceed as follows. This is a Monte-Carlo significance test, and a useful strategy. 1) use ccf() to compute the cross-correlation between x and y. 2) repeat the following steps, say, 1000 times. 2a) randomly reorder the values of one of the time series, say x. Call the randomly reordered series x'. 2b) use ccf() to compute the cross-correlation between x' and y. Store that cross-correlation. 3) the 1000 cross-correlation estimates computed in step 2 are all estimating cross-correlation 0, conditional on the data. A two-tailed test then is: if the cross-correlation computed in step 1 is outside the (0.025, 0.975) quantiles of the empirical distribution of the cross-correlations computed in step 2, then, reject the null hypothesis that x and y are uncorrelated, with size 0.05. I hope that this helps. Andrew Juni Joshi wrote: Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not provide the confidence intervals of cross correlation. Is there any function that calculates the confidence interval of correlation between two time series data or performs the test of no correlation between two time series data. Thanks. Jun __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 Email: [EMAIL PROTECTED] http://www.ms.unimelb.edu.au __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Cross-correlation between two time series data
Hi, Andrew: This will produce a permutation distribution for the correlation under the null hypothesis of zero correlation between the variables. This is a reasonable thing to do, and would probably produce limits more accurate than the dashed red lines on the 'ccf' plot. However, they would NOT be confidence interval(s). For a confidence interval on cross correlation, you'd have to hypothesize some cross correlation pattern between x and y, preferably parameterized parsimoniously, then somehow determine an appropriate range of values consistent with the data. By the time you've done all that, you've effectively fit some model and constructed confidence intervals on the parameter(s). Best Wishes, Spencer Andrew Robinson wrote: Jun, If your interest is to estimate the correlation and either a confidence interval or a test for no correlation, then you might try to proceed as follows. This is a Monte-Carlo significance test, and a useful strategy. 1) use ccf() to compute the cross-correlation between x and y. 2) repeat the following steps, say, 1000 times. 2a) randomly reorder the values of one of the time series, say x. Call the randomly reordered series x'. 2b) use ccf() to compute the cross-correlation between x' and y. Store that cross-correlation. 3) the 1000 cross-correlation estimates computed in step 2 are all estimating cross-correlation 0, conditional on the data. A two-tailed test then is: if the cross-correlation computed in step 1 is outside the (0.025, 0.975) quantiles of the empirical distribution of the cross-correlations computed in step 2, then, reject the null hypothesis that x and y are uncorrelated, with size 0.05. I hope that this helps. Andrew Juni Joshi wrote: Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not provide the confidence intervals of cross correlation. Is there any function that calculates the confidence interval of correlation between two time series data or performs the test of no correlation between two time series data. Thanks. Jun __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Cross-correlation between two time series data
Hi Spencer, you are quite right. I should have been careful to emphasize that the strategy I suggested was intended only to produce the test for no correlation clause of the either a confidence interval or a test for no correlation sentence. Cheers Andrew On Mon, Sep 04, 2006 at 04:00:44PM -0700, Spencer Graves wrote: Hi, Andrew: This will produce a permutation distribution for the correlation under the null hypothesis of zero correlation between the variables. This is a reasonable thing to do, and would probably produce limits more accurate than the dashed red lines on the 'ccf' plot. However, they would NOT be confidence interval(s). For a confidence interval on cross correlation, you'd have to hypothesize some cross correlation pattern between x and y, preferably parameterized parsimoniously, then somehow determine an appropriate range of values consistent with the data. By the time you've done all that, you've effectively fit some model and constructed confidence intervals on the parameter(s). Best Wishes, Spencer Andrew Robinson wrote: Jun, If your interest is to estimate the correlation and either a confidence interval or a test for no correlation, then you might try to proceed as follows. This is a Monte-Carlo significance test, and a useful strategy. 1) use ccf() to compute the cross-correlation between x and y. 2) repeat the following steps, say, 1000 times. 2a) randomly reorder the values of one of the time series, say x. Call the randomly reordered series x'. 2b) use ccf() to compute the cross-correlation between x' and y. Store that cross-correlation. 3) the 1000 cross-correlation estimates computed in step 2 are all estimating cross-correlation 0, conditional on the data. A two-tailed test then is: if the cross-correlation computed in step 1 is outside the (0.025, 0.975) quantiles of the empirical distribution of the cross-correlations computed in step 2, then, reject the null hypothesis that x and y are uncorrelated, with size 0.05. I hope that this helps. Andrew Juni Joshi wrote: Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not provide the confidence intervals of cross correlation. Is there any function that calculates the confidence interval of correlation between two time series data or performs the test of no correlation between two time series data. Thanks. Jun __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Andrew Robinson Department of Mathematics and StatisticsTel: +61-3-8344-9763 University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599 Email: [EMAIL PROTECTED] http://www.ms.unimelb.edu.au __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Cross-correlation between two time series data
Hi all, I have two time series data (say x and y). I am interested to calculate the correlation between them and its confidence interval (or to test no correlation). Function cor.test(x,y) does the test of no correlation. But this test probably is wrong because of autocorrelated data. ccf() calculates the correlation between two series data. But it does not provide the confidence intervals of cross correlation. Is there any function that calculates the confidence interval of correlation between two time series data or performs the test of no correlation between two time series data. Thanks. Jun __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
