Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.9818182 Very strong positive correlation! the "x" is increasing Now, I would like to resample this time series because I have others time series where the trend is more "uncertain" and the sample size is still small. I read "Resampling Methods in R: The boot Package (ISSN 1609-3631)" and I believe that a way of doing it is by a block bootstrap that allows to deal with the autocorrelation (I know that some of my time series show autocorrelation, lag=1). I used "trend.test" function (library=pastecs) and I did: >trend.x=trend.test(x[-c(4,10)],R=999) >trend.x >trend.x$p.value >plot(trend.x) And I get: > trend.x=trend.test(x[-c(4,10)],R=999) > trend.x BLOCK BOOTSTRAP FOR TIME SERIES Fixed Block Length of 1 Call: tsboot(tseries = x, statistic = test.trend, R = R, l = 1, sim = "fixed") Bootstrap Statistics : original bias std. error t1* 0.9818182 -0.9844001 0.3272114 > trend.x$p.value [1] 0 I suppose that the problem arises from the length of the block (1) and in this way I get a rho=0, (nevertheless I don't understand how it is significant). I would like to change the block length but I am not able to (I tried in several different ways but unsuccessfully). So, two questions: 1) How can I change the block length? 2) In terms of block length and type of simulation (sim="fixed" or "geom"), what is the best way of doing it? Thanks in advance for any suggestion, Best wishes Simone ¿Quieres conocerte mejor? ¡Conoce lo que Windows Live tiene especialmente para ti! _________________________________________________________________ [[elided Hotmail spam]] [[alternative HTML version deleted]]
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