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New results in linear filtering and prediction theory
 TRANS. ASME, SER. D, J. BASIC ENG
, 1961
"... A nonlinear differential equation of the Riccati type is derived for the covariance matrix of the optimal filtering error. The solution of this "variance equation " completely specifies the optimal filter for either finite or infinite smoothing intervals and stationary or nonstationary sta ..."
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Cited by 607 (0 self)
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A nonlinear differential equation of the Riccati type is derived for the covariance matrix of the optimal filtering error. The solution of this "variance equation " completely specifies the optimal filter for either finite or infinite smoothing intervals and stationary or nonstationary
The rendering equation
 Computer Graphics
, 1986
"... ABSTRACT. We present an integral equation which generallzes a variety of known rendering algorithms. In the course of discussing a monte carlo solution we also present a new form of variance reduction, called Hierarchical sampling and give a number of elaborations shows that it may be an efficient n ..."
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Cited by 912 (0 self)
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ABSTRACT. We present an integral equation which generallzes a variety of known rendering algorithms. In the course of discussing a monte carlo solution we also present a new form of variance reduction, called Hierarchical sampling and give a number of elaborations shows that it may be an efficient
Generalized Autoregressive Conditional Heteroskedasticity
 JOURNAL OF ECONOMETRICS
, 1986
"... A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametri ..."
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Cited by 2406 (30 self)
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A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class
Longitudinal data analysis using generalized linear models”.
 Biometrika,
, 1986
"... SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating ..."
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Cited by 1526 (8 self)
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SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence
The theory of planned behavior
 Organizational Behavior and Human Decision Processes
, 1991
"... Research dealing with various aspects of * the theory of planned behavior (Ajzen, 1985, 1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is found to be well supported by empirical evidence. Intentions to perform behaviors of different kinds can be predicted wit ..."
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Cited by 2754 (9 self)
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with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior. Attitudes, subjective norms, and perceived behavioral control are shown
Monopolistic competition and optimum product diversity. The American Economic Review,
, 1977
"... The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper is c ..."
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Cited by 1911 (5 self)
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is concerned with the last of these. The basic principle is easily stated.' A commodity should be produced if the costs can be covered by the sum of revenues and a properly defined measure of consumer's surplus. The optimum amount is then found by equating the demand price and the marginal cost
On the distribution of the largest eigenvalue in principal components analysis
 ANN. STATIST
, 2001
"... Let x �1 � denote the square of the largest singular value of an n × p matrix X, all of whose entries are independent standard Gaussian variates. Equivalently, x �1 � is the largest principal component variance of the covariance matrix X ′ X, or the largest eigenvalue of a pvariate Wishart distribu ..."
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Cited by 422 (4 self)
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Let x �1 � denote the square of the largest singular value of an n × p matrix X, all of whose entries are independent standard Gaussian variates. Equivalently, x �1 � is the largest principal component variance of the covariance matrix X ′ X, or the largest eigenvalue of a pvariate Wishart
From recombination of genes to the estimation of distributions I. binary parameters
, 1996
"... The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the fitness of the population has to be estimated. For the usual sexual recombination the computation can be difficult. In this paper we shortly ..."
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Cited by 312 (9 self)
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The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the fitness of the population has to be estimated. For the usual sexual recombination the computation can be difficult. In this paper we
Variance
, 2008
"... This study examines the significant impact of exchange rate shock on prices of Malaysian imports and exports. In methodology, the study adopts vector error correction (VECM) model using monthly data of nominal exchange rates, money supply, prices of imports and prices of exports covering the period ..."
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of M1:1999 to M12:2006. For further analysis, we adopt an innovation accounting by simulating variance decompositions (VDC) and impulse response functions (IRF). VDC and IRF serve as tools for evaluating the dynamic interactions and strength of causal relations among variables in the system. In fact
Results 1  10
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233,871