Concept
Exponential smoothing
Related publications (20)
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
Ekaterina Krymova, Nicola Parolini, Andrea Kraus, David Kraus, Daniel Lopez, Markus Scholz, Tao Sun
Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...
eLIFE SCIENCES PUBL LTD2023Model-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 ...
SPRINGER2022Testing For The Rank Of A Covariance Operator
How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...
INST MATHEMATICAL STATISTICS-IMS2022Sparsely Observed Functional Time Series: Theory and Applications
Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...
EPFL2021Functional lagged regression with sparse noisy observations
A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions. In practice, the underlying regressor curve time series are not always ...
WILEY2020Application of Time Series Methods on Long-Term Structural Monitoring Data for Fatigue Analysis
Eugen Brühwiler, Bartlomiej Wojciech Sawicki, Morteza Ahmadivala
Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...
2019Long-term path prediction in urban scenarios using circular distributions
Human ability to foresee the near future plays a key role in everyone's life to prevent potentially dangerous situations. To be able to make predictions is crucial when people have to interact with the surrounding environment. Modeling such capability can ...
2018Workflow to Establish Time-Specific Zones in Precision Agriculture by Spatiotemporal Integration of Plant and Soil Sensing Data
Management zones (MZs) are used in precision agriculture to diversify agronomic management across a field. According to current common practices, MZs are often spatially static: they are developed once and used thereafter. However, the soil–plant relations ...
2018Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models
Sylvain Calinon, Ajay Kumar Tanwani, Swati Krishnan
Generalizing manipulation skills to new situations requires extracting invariant patterns from demonstrations. For example, the robot needs to understand the demonstrations at a higher level while being invariant to the appearance of the objects, geometric ...
2018AUTOREGRESSIVE MOVING AVERAGE GRAPH FILTERS A STABLE DISTRIBUTED IMPLEMENTATION
We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come ...
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