Results 41 to 50 of about 147,262 (309)

Quasi Score is more efficient than Corrected Score in a general nonlinear measurement error model [PDF]

, 2005
We compare two consistent estimators of the parameter vector beta of a general exponential family measurement error model with respect to their relative efficiency.
Kukush, Alexander, A. Kukush, Shklyar, Sergiy, S. Shklyar, H. Schneeweiss, Schneeweiß, Hans   +5 more
core   +1 more source

Covariate Balancing With Measurement Error

Statistics in Medicine
ABSTRACT In recent years, there is a growing body of causal inference literature focusing on covariate balancing methods. These methods eliminate observed confounding by equalizing covariate moments between the treated and control groups.
Xialing Wen, Ying Yan
openaire   +3 more sources

Inverse probability weighting with error-prone covariates [PDF]

Biometrika, 2013
Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which
Daniel F. McCaffrey, J. R. Lockwood, Claude M. Setodji   +2 more
openaire   +3 more sources

On the Approximation of Precision Matrices for Wide-Swath Altimetry

Remote Sensing
New observations of ocean surface topography obtained by wide-swath satellite interferometry require new capabilities to process spatially correlated errors in order to assimilate these data into numerical models.
Max Yaremchuk, Christopher Beattie, Gleb Panteleev   +2 more
doaj   +1 more source

Assessing the Quality of Natural Gas Consumption Forecasting: An Application to the Italian Residential Sector

Energies, 2017
(1) Background: The present paper aims at estimating the quality of the forecasts obtained by using one equation models. In particular, the focus is on the effect that the explanatory variables have on the forecasted quantity.
Federico Scarpa, Vincenzo Bianco
doaj   +1 more source

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization. [PDF]

PLoS ONE, 2013
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models.
Daniel Bartz, Kerr Hatrick, Christian W Hesse, Klaus-Robert Müller, Steven Lemm   +4 more
doaj   +1 more source

Optimal solution error covariance in highly nonlinear problems of variational data assimilation

, 2012
The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem (see, e.g.[1]) to find the initial condition, boundary conditions or model parameters.
Le Dimet, F.X., G. J. M. Copeland, Shutyaev, V., Gejadze, Igor, F.-X. Le Dimet, V. Shutyaev, I. Gejadze, Shutyaev, Victor P., Copeland, G., Le Dimet, François-Xavier, Gejadze, I, Copeland, G.J.M   +11 more
core   +1 more source

Measurement Sensitivity and Estimation Error in Distribution System State Estimation using Augmented Complex Kalman Filter

Journal of Modern Power Systems and Clean Energy, 2020
Distribution state estimation (DSE) is an essential part of an active distribution network with high level of distributed energy resources. The challenges of accurate DSE with limited measurement data is a well-known problem.
Alan Louis, Gerard Ledwich, Geoff Walker, Yateendra Mishra   +3 more
doaj   +1 more source

Parametric modal regression with error in covariates

Biometrical Journal
AbstractAn inference procedure is proposed to provide consistent estimators of parameters in a modal regression model with a covariate prone to measurement error. A score‐based diagnostic tool exploiting parametric bootstrap is developed to assess adequacy of parametric assumptions imposed on the regression model.
Qingyang Liu, Xianzheng Huang
openaire   +3 more sources

A posteriori error covariances in variational data assimilation

, 2009
The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find some unknown parameters of the model.
Le Dimet, F.X., Gejadze, Igor, Gejadze, I.Y., Shutyaev, Victor P., Russian Foundation for Basic Research (Funder), Le Dimet, François-Xavier, Gejadze, I.Yu., MOISE Project (Funder), Scottish Funding Council via GRPE (Funder), Shutyaev, V., , Scottish Funding Council via GRPE (Funder), Shutyaev, V.P., , Russian Foundation for Basic Research (Funder), , MOISE Project (Funder)   +13 more
core   +1 more source