zyp.trend.vector {zyp} | R Documentation |
Computes a prewhitened linear trend on a vector of data. The zyp package allows you to use either Zhang's method, or the Yue Pilon method of computing nonlinear prewhitened trends.
zyp.trend.vector(data, method=c("yuepilon", "zhang"), conf.intervals=TRUE) zyp.zhang(data, conf.intervals=TRUE) zyp.yuepilon(data, conf.intervals=TRUE)
data |
the input vector. |
method |
the prewhitened trend method to use. |
conf.intervals |
whether to compute confidence intervals. |
This routine computes a prewhitened nonlinear trend on a vector of data, using either Zhang's (described in Wang and Swail, 2001) or Yue Pilon's (describe in Yue Pilon, 2002) method of prewhitening and Sen's slope, and use a Kendall test for significance.
A vector containing the trend and associated data.
lbound |
the lower bound of the trend's confidence interval. |
trend |
the Sen's slope (trend) per unit time. |
trendp |
the Sen's slope (trend) over the time period. |
ubound |
the upper bound of the trend's confidence interval. |
tau |
Kendall's tau statistic computed on the final detrended timeseries. |
sig |
Kendall's P-value computed for the final detrended timeseries. |
nruns |
the number of runs required to converge upon a trend. |
autocor |
the autocorrelation of the final detrended timeseries. |
valid_frac |
the fraction of the data which is valid (not NA) once autocorrelation is removed. |
linear |
the least squares fit trend on the same dat. |
intercept |
the intercept of the Sen's slope (trend). |
zyp.trend.csv
, zyp-package, confint.zyp, zyp.sen.
# Without confidence intervals, using the wrapper routine d <- zyp.trend.vector(c(0, 1, 3, 4, 2, 5), "yuepilon", FALSE) # With confidence intervals, using the wrapper routine d <- zyp.trend.vector(c(0, 1, 3, 4, 2, 5), "yuepilon") # With confidence intervals, not using the wrapper routine d.zhang <- zyp.zhang(c(0, 1, 3, 4, 2, 5)) d.yuepilon <- zyp.yuepilon(c(0, 1, 3, 4, 2, 5))