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Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model

Publications associées (48)

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Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistica ...

2017

For estimating parameters of discrete choice models, observations corresponding to the models are required. In the context of route choice models, we need the information of paths, which are sequences of links and connect between the origin-destination pa ...

2017

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In this paper we aim at integrating the selection of a nesting structure to the maximum likelihood framework of the parameter estimation. Given a finite set of nesting structures, the traditional approach is to estimate the models corresponding to each of ...

2017

This paper addresses the challenging problem of single-channel audio source separation. We introduce a novel userguided framework where source models that govern the separation process are learned on-the-fly from audio examples retrieved online. The user o ...

2017

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Large-scale dynamic models of metabolism remain an overarching ambition of efforts that aim to analyze and explain complex behavior of living entities. However, intrinsic nonlinearity of dynamics of living organisms and structural and quantitative uncertai ...

2016

Beyond Allan Variance - GMWM Framework For Sensor Calibration

Jan Skaloud, Stéphane Guerrier

Proposed 50 years ago for studying stability of oscillators, Allan Variance (AV) was accepted by IEEE as a standard for characterizing behavior of sensors. However, the inverse mapping, i.e. the estimation of noise-parameters from Allan Variance is less st ...

2015

Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the estimation of high-order integer-value ...

American Statistical Association2015

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In this work we investigate the applicability of the wing-aileron-tab model for a bridge section model being actively controlled with leading and trailing edge flaps. The structural and aerodynamic model parameters have been extracted experimentally from a ...

2015

We consider the estimation of an independent and identically distributed (i.i.d.) (possibly non-Gaussian) vector x is an element of R-n from measurements y is an element of R-m obtained by a general cascade model consisting of a known linear transform foll ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

Andrea Rinaldo, Enrico Bertuzzo, Bettina Schaefli, Lorenzo Mari, Flavio Finger

Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alterna- tive intervention mechani ...

2014