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A Structural Error Correction Model
, 2006
"... The Effect of Government Size on the SteadyState Unemployment Rate: ..."
Reconsidering Convergence Rate to Purchasing Power Parity: Structural Error Correction Model Approach
, 2002
"... This paper estimates the speed of the adjustment coefficient in structural error correction models (ECM) and employs a system method for real exchange rates with Hansen and Sargent’s (1980, 1982) IV methods. Empirical results show that the halflives of purchasing power parity deviations are less th ..."
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This paper estimates the speed of the adjustment coefficient in structural error correction models (ECM) and employs a system method for real exchange rates with Hansen and Sargent’s (1980, 1982) IV methods. Empirical results show that the halflives of purchasing power parity deviations are less
Structural Error Correction Models: Instrumental Variables Methods and an Application to an Exchange Rate Model, manuscript
, 1999
"... Error correction models are widely used to estimate dynamic cointegrated systems. In most applications, estimated error correction models are reduced form models. As a result, nonstructural speed of adjustment coefficients are estimated in these applications. A single equation instrumental variable ..."
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Cited by 6 (0 self)
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method can be used to estimate a structural speed of adjustment coefficient. This paper develops a system instrumental variable method to estimate the structural speed of adjustment coefficient in an error correction model. This method utilizes Hansen and Sargent’s (1982) instrumental variable estimator
Improved methods for building protein models in electron density maps and the location of errors in these models. Acta Crystallogr. sect
 A
, 1991
"... Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallographic refinement and result in an incorrect structure. The normally quoted crystallographic residual is often a poor description for the q ..."
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Cited by 1051 (9 self)
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Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallographic refinement and result in an incorrect structure. The normally quoted crystallographic residual is often a poor description
Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification
 Psychological Methods
, 1998
"... This study evaluated the sensitivity of maximum likelihood (ML), generalized least squares (GLS), and asymptotic distributionfree (ADF)based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustn ..."
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Cited by 543 (0 self)
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), and the ML and GLSbased gamma hat, McDonald's centrality index (1989; Me), and rootmeansquare error of approximation (RMSEA) were the most sensitive indices to models with misspecified factor loadings. With ML and GLS methods, we recommend the use of SRMR, supplemented by TLI, BL89, RNI, CFI, gamma
The model checker SPIN.
 IEEE Trans. on Software Eng.
, 1997
"... AbstractSPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from highlevel descriptions of distributed algorithms to detailed code for controlling telephone exchanges. This paper gives an overview of ..."
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Cited by 1516 (26 self)
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AbstractSPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from highlevel descriptions of distributed algorithms to detailed code for controlling telephone exchanges. This paper gives an overview
A review of methods for the assessment of prediction errors in conservation presence/absence models.
 Environmental Conservation
, 1997
"... Summary Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that predict the presence or absence of a species are normally judged by the number of prediction errors. These may be of two types: false positives and false negativ ..."
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Cited by 463 (1 self)
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of prediction accuracy is the number of correctly classified cases. There are other measures of prediction success that may be more appropriate. Strategies for assessing the causes and costs of these errors are discussed. A range of techniques for measuring error in presence/absence models, including some
Bandera: Extracting Finitestate Models from Java Source Code
 IN PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 2000
"... Finitestate verification techniques, such as model checking, have shown promise as a costeffective means for finding defects in hardware designs. To date, the application of these techniques to software has been hindered by several obstacles. Chief among these is the problem of constructing a fini ..."
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Cited by 654 (33 self)
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finitestate model that approximates the executable behavior of the software system of interest. Current bestpractice involves handconstruction of models which is expensive (prohibitive for all but the smallest systems), prone to errors (which can result in misleading verification results
Quantal Response Equilibria For Normal Form Games
 NORMAL FORM GAMES, GAMES AND ECONOMIC BEHAVIOR
, 1995
"... We investigate the use of standard statistical models for quantal choice in a game theoretic setting. Players choose strategies based on relative expected utility, and assume other players do so as well. We define a Quantal Response Equilibrium (QRE) as a fixed point of this process, and establish e ..."
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Cited by 647 (28 self)
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existence. For a logit specification of the error structure, we show that as the error goes to zero, QRE approaches a subset of Nash equilibria and also implies a unique selection from the set of Nash equilibria in generic games. We fit the model to a variety of experimental data sets by using maximum
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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limit performance of "Turbo Codes" codes whose decoding algorithm is equivalent to loopy belief propagation in a chainstructured Bayesian network. In this paper we ask: is there something spe cial about the errorcorrecting code context, or does loopy propagation work as an ap proximate inference scheme
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