• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 25,733
Next 10 →

A Structural Error Correction Model

by Burton A. Abrams, Siyan Wang, Burton A. Abrams , 2006
"... The Effect of Government Size on the Steady-State Unemployment Rate: ..."
Abstract - Add to MetaCart
The Effect of Government Size on the Steady-State Unemployment Rate:

Reconsidering Convergence Rate to Purchasing Power Parity: Structural Error Correction Model Approach

by Jaebeom Kim , 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 half-lives of purchasing power parity deviations are less th ..."
Abstract - Add to MetaCart
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 half-lives of purchasing power parity deviations are less

Structural Error Correction Models: Instrumental Variables Methods and an Application to an Exchange Rate Model, manuscript

by Minseok Young, Jaebeom Kim, Jaebeom Kim, Masao Ogaki, Masao Ogaki, Minseok Yang , 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 ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
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

by T. A. Jones, J. -y. Zou, S. W. Cowan, M. Kjeldgaard - A , 1991
"... Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallo-graphic refinement and result in an incorrect struc-ture. The normally quoted crystallographic residual is often a poor description for the q ..."
Abstract - Cited by 1051 (9 self) - Add to MetaCart
Map interpretation remains a critical step in solving the structure of a macromolecule. Errors introduced at this early stage may persist throughout crystallo-graphic refinement and result in an incorrect struc-ture. The normally quoted crystallographic residual is often a poor description

Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification

by Li-tze Hu, Peter M. Bentler - Psychological Methods , 1998
"... This study evaluated the sensitivity of maximum likelihood (ML)-, generalized least squares (GLS)-, and asymptotic distribution-free (ADF)-based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustn ..."
Abstract - Cited by 543 (0 self) - Add to MetaCart
), and the ML- and GLS-based gamma hat, McDonald's centrality index (1989; Me), and root-mean-square 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, supple-mented by TLI, BL89, RNI, CFI, gamma

The model checker SPIN.

by Gerard J Holzmann - IEEE Trans. on Software Eng. , 1997
"... Abstract-SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level descriptions of distributed algorithms to detailed code for controlling telephone exchanges. This paper gives an overview of ..."
Abstract - Cited by 1516 (26 self) - Add to MetaCart
Abstract-SPIN is an efficient verification system for models of distributed software systems. It has been used to detect design errors in applications ranging from high-level 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.

by Alan H Fielding , John F Bell , Alan H Fielding , John F Bell - 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 ..."
Abstract - Cited by 463 (1 self) - Add to MetaCart
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 Finite-state Models from Java Source Code

by James C. Corbett, Matthew B. Dwyer, John Hatcliff, Shawn Laubach, Corina S. Pasareanu, Hongjun Zheng - IN PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING , 2000
"... Finite-state verification techniques, such as model checking, have shown promise as a cost-effective 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 ..."
Abstract - Cited by 654 (33 self) - Add to MetaCart
finite-state model that approximates the executable behavior of the software system of interest. Current best-practice 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

by Richard D. McKelvey, Thomas R. Palfrey - 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 ..."
Abstract - Cited by 647 (28 self) - Add to MetaCart
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:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - 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 error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
-limit performance of "Turbo Codes" -codes whose decoding algorithm is equivalent to loopy belief propagation in a chain-structured Bayesian network. In this paper we ask: is there something spe cial about the error-correcting code context, or does loopy propagation work as an ap proximate inference scheme
Next 10 →
Results 1 - 10 of 25,733
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2016 The Pennsylvania State University