Computes the Trend of the Ensemble Mean
Computes the trend along the forecast time of the ensemble mean by least
square fitting, and the associated error interval.
Trend() also provides the time series of the detrended ensemble mean
forecasts.
The confidence interval relies on a student-T distribution.
.Trend provides the same functionality but taking a matrix ensemble members
as input (exp).
Trend(var, posTR = 2, interval = 1, siglev = 0.95, conf = TRUE) .Trend(exp, interval = 1, siglev = 0.95, conf = TRUE)
var |
An array of any number of dimensions up to 10. |
posTR |
An integer indicating the position along which to compute the trend. |
interval |
A number of months/years between 2 points along posTR dimension. Set 1 as default. |
siglev |
A numeric value indicating the confidence level for the computation of confidence interval. Set 0.95 as default. |
conf |
A logical value indicating whether to compute the confidence levels or not. Set TRUE as default. |
exp |
An M by N matrix representing M forecasts from N ensemble members. |
$trend |
The intercept and slope coefficients for the least squares fitting of the trend. An array with same dimensions as parameter 'var' except along the posTR dimension, which is replaced by a length 4 (or length 2 if conf = FALSE) dimension, corresponding to the lower limit of the confidence interval (only present if conf = TRUE), the slope, the upper limit of the confidence interval (only present if conf = TRUE), and the intercept. |
$detrended |
Same dimensions as var with linearly detrended var along the posTR dimension. |
Only in .Trend:
$conf.int |
Corresponding to the limits of the |
History:
0.1 - 2011-05 (V. Guemas, virginie.guemas@ic3.cat) - Original code
1.0 - 2013-09 (N. Manubens, nicolau.manubens@ic3.cat) - Formatting to CRAN
2.0 - 2017-02 (A. Hunter, alasdair.hunter@bsc.es) - Adapt to veriApply()
# Load sample data as in Load() example:
example(Load)
months_between_startdates <- 60
trend <- Trend(sampleData$obs, 3, months_between_startdates)
PlotVsLTime(trend$trend, toptitle = "trend", ytitle = "K / (5 year)",
monini = 11, limits = c(-1,1), listexp = c('CMIP5 IC3'),
listobs = c('ERSST'), biglab = FALSE, hlines = 0,
fileout = 'tos_obs_trend.eps')
PlotAno(trend$detrended, NULL, startDates,
toptitle = 'detrended anomalies (along the startdates)', ytitle = 'K',
legends = 'ERSST', biglab = FALSE, fileout = 'tos_detrended_obs.eps')Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.