Showing papers by "Manfred Mudelsee published in 2000"
TL;DR: Examples of time series demonstrate that the presented RAMPFIT approach is useful for practical applications in geosciences, and that the ramp function may serve well to model climate transitions.
123 citations
01 Jan 2000
TL;DR: In this article, a method is proposed for fitting a "ramp" to measured data, which is a continuous function, segmented in three parts: x fitOtUax1 for tRt1, x2 for trt2, and linearly connected between t1 and t2.
Abstract: A method is proposed for fitting a ‘ramp’ to measured data. This is a continuous function, segmented in three parts: x fitOtUax1 for tRt1, x2 for trt2, and linearly connected between t1 and t2. Its purpose is to measure transitions in the mean of time series as they occur, for example, in paleoclimatic records. The unknowns x1 and x2 are estimated by weighted least-squares regression, t1 and t2 by a brute-force search. Computing costs are reduced by several methods. The presented Fortran 77 program, RAMPFIT, includes analysis of weighted ordinary residuals for checking the validity of the ramp form and other assumptions. It fits an AR(1) model to the residuals to measure serial dependency; uneven time spacing is thereby allowed. Three bootstrap resampling schemes (nonparametric stationary, parametric, and wild) provide uncertainties for the estimated parameters. RAMPFIT works interactively (calculation/visualization). Example time series (one artificial, three measured) demonstrate that this approach is useful for practical applications in geosciences (n less than a few hundred, noise, unevenly spaced times), and that the ramp function may serve well to model climate transitions. # 2000 Elsevier Science Ltd. All rights reserved.
105 citations
TL;DR: In this article, the authors examined nonlinear coupling among a number of important climatological variables, d 13 C, d 18 O and insolation, using mutual information and redundancy.
26 citations