Climate Change in Coastal Waters: Time Series Properties Affecting Trend Estimation
نویسندگان
چکیده
منابع مشابه
Estimation of linear trend onset in time series
We propose a method to detect the onset of linear trend in a time series and estimate the change point T from the profile of a linear trend test statistic, computed on consecutive overlapping time windows along the time series. We compare our method to two standard methods for trend change detection and evaluate them with Monte Carlo simulations for different time series lengths, autocorrelatio...
متن کاملSmoothing splines for trend estimation and prediction in time series
We consider the use of generalized additive models with correlated errors for analysing trends in time series. The trend is represented as a smoothing spline so that it can be extrapolated. A method is proposed for choosing the smoothing parameter. It is based on the ability to predict a short term into the future. The choice not only addresses the purpose in hand, but also performs very well, ...
متن کامل1983: Variance Estimation for a Time Series with Linear Trend
The problem of variance estimation for a t ime series with linear trend is studied using model based procedures. The work done by Royall and Cumberland ((2), (3)) is refined and adapted to the special problems of the Current Employment Survey (790 Survey) at the Bureau of Labor Statistics. A variety of variance estimation techniques are examined; including a variation of jackknife estimation an...
متن کاملJump process for the trend estimation of time series
A jump process approach is proposed for the trend estimation of time series. The proposed jump process estimator can locally minimize two important features of a trend, the smoothness and 0delity, and explicitly balance the fundamental tradeo2 between them. A weighted average form of the jump process estimator is derived. The connection of the proposed approach to the Hanning 0lter, Gaussian ke...
متن کاملChange-Point Detection of Climate Time Series by Nonparametric Method
In one of the data mining techniques, change-point detection is of importance in evaluating time series measured in real world. For decades this technique has been developed as a nonlinear dynamics. We apply the method for detecting the change points, Singular Spectrum Transformation (SST), to the climate time series. To know where the structures of climate data sets change can reveal a climate...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Climate
سال: 2016
ISSN: 0894-8755,1520-0442
DOI: 10.1175/jcli-d-16-0014.1