Confidence intervals for Sen slope in zyp-package
On 11/07/2012 12:31 AM, kunger at gfz-potsdam.de wrote:
Hi, I have a question about the computation of confidence intervals in the zyp package, in particular using the functions zyp.sen and confint.zyp, or zyp.yuepilon. (1) I'm a bit confused about the confidence intervals given by zyp.sen and confint.zyp. When I request a certain confidence interval in the function, the R output seems to deliver another confidence interval, e.g. when I set level=0.95 in the function, then the output is for 0.025 and 0.975 (instead of the expected 0.05 and 0.95). See example below. Which confint statement is the right one? (2) I checked the documentation but did not find a specification about which confidence interval is used in the zyp.yuepilon function. It seems to be the same as level=0.95 in confint.zyp (I'm not sure if this is 0.95 or 0.975 - see above). Maybe, I'm just not seeing the obvious explanation... Could anybody advise me? Thanks in advance, Katy --- My example:
x<- c(0, 1, 2, 3, 4, 5) y<- c(6, 4, 1, 8, 7, 8)
# zyp.sen and confint.zyp function
slope<- zyp.sen(y~x) slope$coef
Intercept x 4.5000000 0.6666667
ci_99<- confint.zyp(slope, level=0.99) ci_99
0.005 0.995
Intercept -2.071288 10.07129
x -3.000000 3.00000
ci_95<- confint.zyp(slope, level=0.95) ci_95
0.025 0.975
Intercept -0.6196794 8.619679
x -2.5000000 2.333333
ci_90<- confint.zyp(slope, level=0.90) ci_90
0.05 0.95
Intercept 0.1230428 7.876957
x -2.0000000 2.000000
# zyp.yuepilon
# confidence interval corresponds to nominal 0.95 interval in confint.zyp (output 0.025 0.975)
xy_senslope<- zyp.yuepilon (y, conf.intervals=TRUE) xy_senslope
lbound trend trendp ubound tau sig nruns autocor valid_frac
-2.50000000 0.66666667 4.00000000 2.33333333 0.80000001 0.08641075 1.00000000 -0.22400000 1.00000000
linear intercept
0.74285714 3.83333333
Hi Katy, I didn't see an answer to this, so I'll attempt one. A 95% confidence interval is defined as an interval within which 95% of replicated values will fall. In most cases, the preferred confidence interval among the many which could be calculated is symmetric about the observed value in the sense that half of the replicated values are expected to fall above the observed value and half below. This means that 2.5% of replications would be expected to produce values below the lower confidence limit and 2.5% above the upper one. If these proportions were 5% below and 5% above, you would get a 90% confidence interval. Jim