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  • Search: subject:"Collinear"
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Year of publication
Subject
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Bayesian identification 3 highly collinear regressors 3 multicollinear regressions 3 weakly identified regression coefficients 3 Estimation theory 2 Regression analysis 2 Regressionsanalyse 2 Schätztheorie 2 Asymptotically collinear regressors 1 Bayes-Statistik 1 Bayesian inference 1 Factor analysis 1 Faktorenanalyse 1 Lp-approximability 1 Monte Carlo experiment 1 Multiplier 1 Multiplikator 1 OLS estimator 1 Positive semidefinite 1 Statistical test 1 Statistical theory 1 Statistische Methodenlehre 1 Statistischer Test 1 Students 1 Studierende 1 Transformed Form of Student Test statistics 1 adjusted multiplier 1 asymptotic distribution 1 coefficient of collinear refraction 1 cointegration 1 computer program 1 correlated random variables 1 correlation matrix 1 factorial analysis 1 frobenius norm 1 generation of collinear sample data 1 intercorrelation matrix 1 maximum norm 1 multicollinearity 1 multivariate analysis 1
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Online availability
All
Free 6
Type of publication
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Book / Working Paper 5 Article 1
Type of publication (narrower categories)
All
Working Paper 3 Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1
Language
All
English 4 Undetermined 2
Author
All
Pesaran, M. Hashem 3 Smith, Ron P. 2 Mishra, SK 1 Mynbaev, Kairat 1 Pavelescu, Florin-Marius 1 Smith, Ron 1
Institution
All
Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 2
Published in...
All
MPRA Paper 2 BCAM Working Paper 1 CESifo Working Paper 1 CESifo working papers 1 Revista română de economie 1
Source
All
ECONIS (ZBW) 2 EconStor 2 RePEc 2
Showing 1 - 6 of 6
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Posterior Means and Precisions of the Coefficients in Linear Models with Highly Collinear Regressors
Pesaran, M. Hashem; Smith, Ron P. - 2017
linear regression model for both the cases of exactly and highly collinear regressors. We show that in both cases the … precision rises at a slower rate than the sample size. In the highly collinear case, the posterior means converge to normally … statistic for the highly collinear case, which is illustrated with an empirical example. …
Persistent link: https://www.econbiz.de/10011794124
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Posterior means and precisions of the coefficients in linear models with highly collinear regressors
Pesaran, M. Hashem; Smith, Ron - 2017
linear regression model for both the cases of exactly and highly collinear regressors. We show that in both cases the … precision rises at a slower rate than the sample size. In the highly collinear case, the posterior means converge to normally … statistic for the highly collinear case, which is illustrated with an empirical example. …
Persistent link: https://www.econbiz.de/10011771679
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Cover Image
Posterior Means and Precisions of the Coefficients in Linear Models with Highly Collinear Regressors
Pesaran, M. Hashem; Smith, Ron P. - 2017
linear regression model for both the cases of exactly and highly collinear regressors. We show that in both cases the … precision rises at a slower rate than the sample size. In the highly collinear case, the posterior means converge to normally … statistic for the highly collinear case, which is illustrated with an empirical example. …
Persistent link: https://www.econbiz.de/10015404652
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Cover Image
Modelling factors of Student test statistics dispersion in a multiple linear regression
Pavelescu, Florin-Marius - In: Revista română de economie 41 (2015) 2, pp. 25-41
Persistent link: https://www.econbiz.de/10011545876
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Regressions with Asymptotically Collinear Regressor
Mynbaev, Kairat - Volkswirtschaftliche Fakultät, … - 2009
We investigate the asymptotic behavior of the OLS estimator for regressions with two slowly varying regressors. It is shown that the asymptotic distribution is normal one-dimensional and may belong to one of four types depending on the relative rates of growth of the regressors. The analysis...
Persistent link: https://www.econbiz.de/10009132740
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On generating correlated random variables with a given valid or invalid Correlation matrix
Mishra, SK - Volkswirtschaftliche Fakultät, … - 2004
In simulation we often have to generate correlated random variables by giving a reference intercorrelation matrix, R or Q. The matrix R is positive definite and a valid correlation matrix. The matrix Q may appear to be a correlation matrix but it may be invalid (negative definite). With R(m,m)...
Persistent link: https://www.econbiz.de/10005787098
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