Least squares estimation is discussed from the point of view of a statistician. Much of the emphasis is on problems encountered in application and, more specifically, on questions involving assumptions: what assumptions are needed, when are they needed, what happens if they are not valid, and if they are invalid, how that fact can be detected
Abstract:Through theoretical derivation, some properties of the total least squares estimation are f...
RMSE based methods distort circular error estimates (up to 50% overestimation). The empirical approa...
Data resolution is an important task in astronomy, one that is generally undertaken using the method...
Least squares method theory and application to curve fitting, data smoothing, and solution of overde...
Least squares, minimum variance, and Kalman estimation applied to mathematical model of free flight ...
Artículo de publicación ISIWe characterize the performance of the widely used least-squares estimato...
Equations are presented which attempt to fit least squares polynomials to tables of date. It is conc...
Gravity measurements at stations in northwestern Nigeria were assumed to be random variables. Gravit...
An extension of the method of Jaynes, whereby least biased probability estimates are obtained, permi...
The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown...
Thesis (Ph.D.)--University of Washington, 2018We revisit and make progress on some old but challengi...
In variational data assimilation a least squares objective function is minimised to obtain the most ...
Bayesian estimation, decision theory, least squares method, maximum likelihood, and other mathematic...
Least squares technique and curve fitting subroutine for backscatter data analysi
Least-squares estimation methods are perhaps the most widely used tool in all fields of geodetic res...
Abstract:Through theoretical derivation, some properties of the total least squares estimation are f...
RMSE based methods distort circular error estimates (up to 50% overestimation). The empirical approa...
Data resolution is an important task in astronomy, one that is generally undertaken using the method...
Least squares method theory and application to curve fitting, data smoothing, and solution of overde...
Least squares, minimum variance, and Kalman estimation applied to mathematical model of free flight ...
Artículo de publicación ISIWe characterize the performance of the widely used least-squares estimato...
Equations are presented which attempt to fit least squares polynomials to tables of date. It is conc...
Gravity measurements at stations in northwestern Nigeria were assumed to be random variables. Gravit...
An extension of the method of Jaynes, whereby least biased probability estimates are obtained, permi...
The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown...
Thesis (Ph.D.)--University of Washington, 2018We revisit and make progress on some old but challengi...
In variational data assimilation a least squares objective function is minimised to obtain the most ...
Bayesian estimation, decision theory, least squares method, maximum likelihood, and other mathematic...
Least squares technique and curve fitting subroutine for backscatter data analysi
Least-squares estimation methods are perhaps the most widely used tool in all fields of geodetic res...
Abstract:Through theoretical derivation, some properties of the total least squares estimation are f...
RMSE based methods distort circular error estimates (up to 50% overestimation). The empirical approa...
Data resolution is an important task in astronomy, one that is generally undertaken using the method...