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KALMANTYPE RECURSIONS FOR TIMEVARYING ARMA MODELS AND THEIR IMPLICATION FOR LEAST SQUARES PROCEDURE∗ BY
"... Abstract. This paper is devoted to ARMA models with timedependent coefficients, including wellknown periodic ARMA models. We provide statespace representations and Kalmantype recursions to derive a Wold–Cramér decomposition for the least squares residuals. This decomposition turns out to be ver ..."
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Abstract. This paper is devoted to ARMA models with timedependent coefficients, including wellknown periodic ARMA models. We provide statespace representations and Kalmantype recursions to derive a Wold–Cramér decomposition for the least squares residuals. This decomposition turns out
Maxwell equations in matrix form, squaring procedure, separating the variables, and structure of electromagnetic solutions
, 2009
"... The Riemann–Silberstein–Majorana–Oppenheimer approach to the Maxwell ..."
Adjustment of Frequently Used Chisquare Procedures for the Effect of SitetoSite Dependencies in the Analysis of Dental Data
"... On behalf of: ..."
Robust Solutions To LeastSquares Problems With Uncertain Data
, 1997
"... . We consider leastsquares problems where the coefficient matrices A; b are unknownbutbounded. We minimize the worstcase residual error using (convex) secondorder cone programming, yielding an algorithm with complexity similar to one singular value decomposition of A. The method can be interpret ..."
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Cited by 205 (14 self)
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. We consider leastsquares problems where the coefficient matrices A; b are unknownbutbounded. We minimize the worstcase residual error using (convex) secondorder cone programming, yielding an algorithm with complexity similar to one singular value decomposition of A. The method can
CoArray Fortran for parallel programming
 ACM FORTRAN FORUM
, 1998
"... CoArray Fortran, formerly known as F, is a small extension of Fortran 95 for parallel processing. A CoArray Fortran program is interpreted as if it were replicated a number of times and all copies were executed asynchronously. Each copy has its own set of data objects and is termed an image. The ..."
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Cited by 278 (7 self)
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. Only where there are square brackets, or where there is a procedure call and the procedure contains square brackets, is communication between images involved. There are intrinsic procedures to synchronize images, return the number of images, and return the index of the current image. We introduce
A Least Squares Procedure of Direct Estimation of Azimuth and Velocity of a Propagating Wave. Alexandria Laboratories Report No. AL701
, 1970
"... ab ' rMT.Hr»Ro?0PORT NO'S ' <Any C"h " numb"'',""n'y 6 « "'l*"d 2]llll2ÄAP5 Approved for public release; distribution unlimited. ..."
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Cited by 1 (0 self)
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ab ' rMT.Hr»Ro?0PORT NO'S ' <Any C"h " numb"'',""n'y 6 « "'l*"d 2]llll2ÄAP5 Approved for public release; distribution unlimited.
Stochastic Gradient Boosting
 Computational Statistics and Data Analysis
, 1999
"... Gradient boosting constructs additive regression models by sequentially fitting a simple parameterized function (base learner) to current "pseudo"residuals by leastsquares at each iteration. The pseudoresiduals are the gradient of the loss functional being minimized, with respect to ..."
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Cited by 285 (1 self)
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Gradient boosting constructs additive regression models by sequentially fitting a simple parameterized function (base learner) to current "pseudo"residuals by leastsquares at each iteration. The pseudoresiduals are the gradient of the loss functional being minimized, with respect
Independent Factor Analysis
 Neural Computation
, 1999
"... We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square no ..."
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Cited by 277 (9 self)
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We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square
Adaptive Least Squares Correlation: A Powerful Image Matching Technique
 South African Journal of Photogrammetry, Remote Sensing and Cartography
, 1985
"... The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its application to image matching is outlined. It allows for simultaneous radiometric corrections and local geometrical image shaping, whereby the system parameters are automa ..."
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Cited by 182 (31 self)
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are automatically assessed, corrected, and thus optimized during the least squares iterations. The various tools of least squares estimation can be favourably utilized for the assessment of the correlation quality. Furthermore, the system allows for stabilization and improvement of the correlation procedure through
A simplified method of evaluating dose effect experiments
 Journal of Pharmacology and Experimental Therapeutics
, 1949
"... The increased emphasis on quantitative biological studies in recent years has resulted in the widespread use of statistical methods for evaluating biological data. Much of this data is of the allornone type and, consequently, it is necessary to solve a doseper cent effect curve. By converting do ..."
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Cited by 255 (0 self)
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doses to logarithms and per cent effects to probits (1), logits (2), or angles (3), a straight line may be fitted by the method of weighted least squares. From the viewpoint of many biologists, such procedures are not pleasant to contemplate because the data must be converted to units which
Results 11  20
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5,153