Concept

Trend-stationary process

Related publications (19)

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Elevated nitrate from human activity causes ecosystem and economic harm globally. The factors that control the spatiotemporal dynamics of riverine nitrate concentration remain difficult to describe and predict. We analyzed nitrate concentration from 4450 s ...

SPRINGER2022

Trends in the Extremes of Environments Associated with Severe US Thunderstorms

Anthony Christopher Davison, Erwan Fabrice Koch, Jonathan Koh Boon Han

Severe thunderstorms can have devastating impacts. Concurrently high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are known to be conducive to severe weather, so high values of PROD - (CAPE)(1/2) x SRH have been ...

AMER METEOROLOGICAL SOC2021

Sparsely observed functional time series: estimation and prediction

Victor Panaretos, Tomas Rubin

Functional time series analysis, whether based on time or frequency domain methodology, has traditionally been carried out under the assumption of complete observation of the constituent series of curves, assumed stationary. Nevertheless, as is often the c ...

INST MATHEMATICAL STATISTICS2020

Bayesian Uncertainty Management in Temporal Dependence of Extremes

Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn

Both marginal and dependence features must be described when modelling the extremes of a stationary time series. There are standard approaches to marginal modelling, but long- and short-range dependence of extremes may both appear. In applications, an assu ...

Springer Verlag2016

Bayesian uncertainty management in temporal dependence of extremes

Anthony Christopher Davison, Thomas Lugrin, Jonathan A. Tawn

Both marginal and dependence features must be described when modelling the extremes of a stationary time series. There are standard approaches to marginal modelling, but long-and short-range dependence of extremes may both appear. In applications, an assum ...

Springer Verlag2016

On the sensitivity of buildings to climate

Parag Rastogi

Building simulation requires a large number of uncertain inputs and parameters. These include quantities that may be known with reasonable confidence, like the thermal properties of materials and building dimensions, but also inputs whose correct values ca ...

EPFL2016

Low-Rank Matrices on Graphs: Generalized Recovery & Applications

Pierre Vandergheynst, Nathanaël Perraudin, Nauman Shahid

Many real world datasets subsume a linear or non-linear low-rank structure in a very low-dimensional space. Unfortunately, one often has very little or no information about the geometry of the space, resulting in a highly under-determined recovery problem. ...

2016

Demodulation of time series highlights impacts of hydrologic drivers on the Everglades ecosystem

Andrea Rinaldo

In the context of climatic uncertainty and potential climatic change, incorporating climatic variability and change in eco-hydrological analysis, as well as understanding the impact of such variability on ecosystems, is of crucial importance. The latter is ...

Wiley-Blackwell2015

What Goes Up Must Come Down? Experimental Evidence on Intuitive Forecasting

Andreas Fuster

Do laboratory subjects correctly perceive the dynamics of a mean-reverting time series? In our experiment, subjects receive historical data and make forecasts at different horizons. The time series process that we use features short-run momentum and long-r ...

2013

Fourier Analysis Of Stationary Time Series In Function Space

Victor Panaretos, Shahin Tavakoli

We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in such a context is the spectral density operator, which gen ...

Institute of Mathematical Statistics2013

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