Search results for "Errors-in-variables models"

Analysis of the sensitivity to the systematic error in least-squares regression models

2004

An algorithm that calculates the sensitivity to the systematic error of the fitted parameters of a least-squares regression model, with respect to the known parameters, is developed. The algorithm can be applied to mechanistic and empirical models, obtained by linear and non-linear regression, including principal component and partial least-squares. It can be useful in identifying those parameters or calibration regions that can influence other parameters and the response mostly, and thus, whose accuracy should be particularly procured. Other applications are the weighing of experimental points and the comparison of different models and regression methods in terms of its ability of amplifyi…

Incorporating Uncertainties into Traffic Simulators

2007

Accounting for Input Noise in Gaussian Process Parameter Retrieval

2020

Gaussian processes (GPs) are a class of Kernel methods that have shown to be very useful in geoscience and remote sensing applications for parameter retrieval, model inversion, and emulation. They are widely used because they are simple, flexible, and provide accurate estimates. GPs are based on a Bayesian statistical framework which provides a posterior probability function for each estimation. Therefore, besides the usual prediction (given in this case by the mean function), GPs come equipped with the possibility to obtain a predictive variance (i.e., error bars, confidence intervals) for each prediction. Unfortunately, the GP formulation usually assumes that there is no noise in the inpu…

Using unsteady-state water level data to estimate channel roughness and discharge hydrograph

2009

A novel methodology for simultaneous discharge and channel roughness estimation is developed and applied to data sets available at three experimental sites. The methodology is based on the synchronous measurement of water level data in two river sections far some kilometers from each other, as well as on the use of a diffusive flow routing solver and does not require any direct velocity measurement. The methodology is first analyzed for the simplest case of a channel with a large slope, where the kinematic assumption holds. A sensitivity and a model error analysis are carried out in this hypothesis in order to show the stability of the results with respect to the error in the input paramete…

HUMAN CAPITAL IN GROWTH REGRESSIONS: HOW MUCH DIFFERENCE DOES DATA QUALITY MAKE?.

2000

We construct a revised version of the Barro and Lee (1996) data set for a sample of OECD countries using previously unexploited sources and following a heuristic approach to obtain plausible time profiles for attainment levels by removing sharp breaks in the data that seem to reflect changes in classification criteria. It is then shown that these revised data perform much better than the Barro and Lee (1996) or Nehru et al (1995) series in a number of growth specifications. We interpret these results as an indication that poor data quality may be behind counterintuitive findings in the recent literature on the (lack of) relationship between educational investment and growth. Using our prefe…

Fuel cell modelling and test: Experimental validation of model accuracy

2013

In the last few years, renewable energies have been encouraged by worldwide governments to meet energy saving policies. Among renewable energy sources, fuel cells have attracted much interest for a wide variety of research areas. Fuel cell-based residential-scaled power supply systems take advantage of simultaneous generation of power and heat, reducing the overall fossil fuel consumption and utilities cost. Modeling is one of the most important topics concerning fuel cell use. In this paper, a measurement-based steady-state and dynamic fuel cell model is presented. The proposed modelling approach is implemented on a 5kW Proton Exchange Membrane Fuel Cell. The parameters identification proc…

MATLAB-based simulator of a 5 kW fuel cell for power electronics design

2013

Abstract In the last few years, renewable energies have been encouraged by worldwide governments to meet energy saving policies. Among renewable energy sources, fuel cells have attracted much interest for a wide variety of research areas. Since combined heat-power generation is allowed, household appliances are still the most promising applications. Fuel cell-based residential-scaled power supply systems take advantage by simultaneous generation of power and heat, reducing the overall fossil fuel consumption and utilities cost. Modelling is one of the most important topic concerning fuel cell use. In this paper, a measurement-based steady-state and dynamic fuel cell model is presented. The …

Selection of the Best Subset of Variables in Regression and Time Series Models

2009

The problem of variable selection is one of the most pervasive model selection problems in statistical applications. Often referred to as the problem of subset selection, it arises when one wants to model the relationship between a variable of interest and a subset of potential explanatory variables or predictors, but there is uncertainty about which subset to use. Several papers have dealt with various aspects of the problem but it appears that the typical regression user has not benefited appreciably. One reason for the lack of resolution of the problem is the fact that it is has not been well defined. Indeed, it is apparent that there is not a single problem, but rather several problems …