W. E. Deming, Statistical Adjustment of Data. New York: Wiley, 1946.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....as H = H 1H, where H and 1H represent the known and unknown parts of H, respectively. The method of total least squares (TLS) or error in variables regression, has been shown to be an effective technique for solving the set of equations in (1) where both H and g are contaminated with noise [1] [3] For shift invariant blurs, the special structure of H and 1H can be exploited in the constrained TLS (CTLS) technique [4] to obtain better estimates. Recently, a regularized version of CTLS was demonstrated in [5] which attempts to preserve smoothness properties of the signal through the ....

W. E. Deming, Statistical Adjustment of Data. New York: Wiley, 1946.

....easy to detect just by going through the raw data or scatter plots. However the size and complexity of large data sets makes visual scanning an infeasible screening method. Some analysts adopt ad hoc methods borrowed from quality control techniques used in manufacturing. William Edwards Deming [4], pioneered the field of quality control based on the work of Walter Shewhart [12] While effective for process control in engineering and manufacturing, these methods do not translate well to immediate detection of inconsistencies in large complex data sets, especially for multivariate data. ....

Deming, W. E. (1943). Statistical Adjustment of Data. John Wiley, New York .

....however, this dependency between x i and y is not a priori known, and has to be determined experimentally. There exist many methods and algorithms that extract the dependency from the experimental data. There exist many statistical methods that help us to discover such a dependency (see, e.g. (Deming 1964)) To apply them, we must have several situations in which we know both y and x i . So, we have the values x 11 ; xn1 ; y 1 that correspond to the first situation, the values x 21 ; x 2n ; y 2 that were measured in the second situation, and, finally, the values xN1 ; ....

Deming, W. E. 1964. Statistical adjustment of data.

....from the internal evidence in the data, and always gives accuracy estimates which correspond nicely with the indications of common sense) Unfortunately, Wald died in an airplane accident, so soon after his conversion to Bayesianity that he had no opportunity to correct this early attempt. W. E. Deming (1943) concluded that the problem is fundamentally indeterminate and that it is necessary to know the ratio = oe y =oe x in order to make any estimates of ff; fi . Then he estimated them by minimizing the sum of squares X i h 2 (x i Gamma X i ) 2 (y i Gamma Y i ) 2 i (1) with ....

Deming, W. E. (1943), Statistical Adjustment of Data, J. Wiley, New York.

....model when the metric is Euclidean . In more complicated problems, for example when the data points involve more than two quantities measured with error, each of Eqs. 10) has an obvious generalization (see, e.g. Zamar 1985, 1987) To solve the minimization problem, we follow Deming (1938) and Brown (1952) in recognizing that the residual vector v as well as the vector a of explanatory parameters are both free variables. In the statistical literature the v are known as incidental parameters. Since this is a problem in constrained minima, we introduce a p vector l of Lagrange ....

Deming, W. E. (1938). Statistical Adjustment of Data. New York: John Wiley & Sons, Inc.

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W. E. Deming, Statistical Adjustment of Data. New York: Wiley, 1946.

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W. E. Deming, Statistical adjustment of data, Dover, N.Y., 1964.

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