While parameter bounding methods and algorithms have been extensively developed in the case of exactly known regressor variables, little attention has been paid to the bounded errors-in-variables problem. This chapter gives a formal proof of a previous result on the description of the feasible ...
Classical Errors-in-Variablesmultiple indicator methodInstrumental variable techniquesTwo measures of an error-ridden explanatory variable make it possible to solve the classical errors-in-variable problem by using one measure as an instrument for the other. It is well known that a second IV estimate...
The usual assumption in the classical errors-in-variables problem of independent measurement errors cannot necessarily be maintained when the data are time series; errors may be strongly serially correlated, possibly containing seasonal effects and trends. When it is possible to identify frequency bands...
errors-in-variablesbias(Xismeasuredwitherror). InstrumentalvariablesregressioncaneliminatebiaswhenE(u|X)≠0-usinganinstrumentalvariable,Z. OneRegressorandOneInstrument Loosely,IVregressionbreaksXintotwoparts:apartthatmightbecorrelatedwithu,andapartthatisnot.Byisolatingthepartthatisnotcorrelatedwithu,itispossibleto...
The problem of estimating unknown parameters in an errors-in-variables model (EVM)has been extensively discussed in the literature while relatively little has been concerned with the prediction problem in the EVM context. In this paper the integrated mean square, error of prediction (TMSE) is ...
The paper gives an overview of errors-in-variables methods in system identification. Background and motivation are given. Simple examples illustrate why the identification problem can be difficult. Under general weak assumptions, the systems are not uniquely identifiable, but can be parameterized using...
A consistent estimator in general functional errors-in-variables models The problem of estimation in nonlinear functional errors-in-variables model is considered. A modified least squares estimator is studied, its consistency a... S Baran - 《Metrika》 被引量: 27发表: 2000年 加载更多来源...
When using shared variables in LabVIEW I have observed multiple errors and warnings: What can I do to fix these errors and warnings?Solution LabVIEW shared variables are classified into two types: Single-process shared variables: these are similar to LabVIEW global variables and generally do not...
In this paper, an errors-in-variables (EIV) method is applied to the problem of model estimation for noise cancellation in transient electromagnetic mineral exploration. The algorithm exploits the non-stationary nature of the data. Alternative methods for noise cancellation in these systems rely on...
It has long been known that the Errors-In-Variables (EIV) Model is a special case of the nonlinear Gauss–Helmert Model (GHM) and can, therefore, be adjusted by standard least-squares techniques in iteratively linearized GH-Models, which is the approach by Helmert (Adjustment Computations Base...