Results 211 to 220 of about 629,085 (265)

Error checking with pointer variables

Proceedings of the annual conference on - ACM 76, 1976
The use of pointer variables in a programming language often results in a difficult class of errors to detect. Pointers may point to storage that no longer is allocated, or storage may be allocated as one data type and accessed as another. This report describes the implementation of pointers in the PLUM PL/1 compiler such that all error conditions are ...
Marvin V. Zelkowitz, Paul R. McMullin, Keith R. Merkel, Howard J. Larsen   +3 more
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Optimal errors-in-variables filtering

Automatica, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guidorzi R., Diversi R., Soverini U.
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Dynamic errors-in-variables systems with three variables

Automatica, 1987
Errors-in-variables problems are considered for the case of three variables, where the underlying relations among the noise-free variables are linear, and covariance information for the noisy variables is available. The static problem where the variables are complex (which can arise when narrowband filtering is used) is analyzed in detail. Some results
Brian D. O. Anderson, Manfred Deistler
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On the identifiability of errors-in-variables models with white measurement errors

Automatica, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
BOTTEGAL, GIULIO, PICCI, GIORGIO, PINZONI, STEFANO   +2 more
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Errors in Variables

1987
This essay surveys the history and recent developments on economic models with errors in variables. These errors may arise from the use of substantive unobservables, such as permanent income, or from ordinary measurement problems in data collection and processing.
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Identifiability of errors in variables dynamic systems

Automatica, 2006
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Juan C. Agüero, Graham C. Goodwin
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Identifiability in dynamic errors-in-variables models

The 22nd IEEE Conference on Decision and Control, 1983
Abstract. This paper is concerned with the identifiability of scalar linear dynamic errors‐in‐variables systems. The analysis is based on second moments only. The set of feasible systems corresponding to given second moments of the observations is described and conditions for identifiability are derived for the case of rational transfer functions.
Anderson, Brian D.O., Deistler, Manfred
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A Note on an 'Errors in Variables' Model

Journal of the American Statistical Association, 1966
Abstract We consider an errors in variables model in which the ‘true’ part of the determining variable is generated by a simple forecasting mechanism. It is shown that the Least Squares errors in variables bias can be interpreted in terms of the parameters of the forecasting mechanism; and that the ‘standard’ result for this bias may no longer hold in ...
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Bootstrapping Errors-in-Variables Models

2000
The bootstrap is a numerical technique, with solid theoretical foundations, to obtain statistical measures about the quality of an estimate by using only the available data. Performance assessment through bootstrap provides the same or better accuracy than the traditional error propagation approach, most often without requiring complex analytical ...
Bogdan Matei, Peter Meer
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Identification in the Linear Errors in Variables Model

Econometrica, 1983
Consider the following multiple linear regression model with errors in variables: \(y_ j=\xi^ T\!_ j\beta +\epsilon_ j\), \(x_ j=\xi_ j+\nu_ j\), \(j=1,...,n\), where \(\xi_ j\), \(x_ j\), \(\nu_ j\), and \(\beta\) are k-vectors, \(y_ j\), \(\epsilon_ j\) are scalars. The \(\xi_ j\) are unobserved variables: instead the \(x_ j\) are observed.
Kapteyn, Arie, Wansbeek, Tom
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