نتایج جستجو برای: seemingly unrelated regressions

تعداد نتایج: 68010  

Journal: :تحقیقات اقتصاد و توسعه کشاورزی ایران 0
مرتضی مولایی استادیار گروه اقتصاد کشاورزی، دانشکدۀ کشاورزی، دانشگاه ارومیه

despite controversy, the contingent valuation method (cvm) is widely used for non-market valuation. among elicitation methods of cvm, the dichotomous choice (dc) has been paid attention. there are two types of dc methods: single-bounded dc (sbdc) and double-bounded dc (dbdc). dbdc is more efficient than sbdc. many of cvm studies in iran used dbdc but data analyses were done by logit model; that...

Journal: :J. Symb. Comput. 2006
Mathias Drton

Seemingly unrelated regressions are statistical regression models based on the Gaussian distribution. They are popular in econometrics but also arise in graphical modeling of multivariate dependencies. In maximum likelihood estimation, the parameters of the model are estimated by maximizing the likelihood function, which maps the parameters to the likelihood of observing the given data. By tran...

Journal: :Applications of Mathematics 2013

1998
Jean-Marie DUFOUR Lynda KHALAF

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR ...

2005
Charles E. Rose

A method was developed for estimating parameters in an individual tree basal area growth model using a system of equations based on dbh rank classes. The estimation method developed is a compromise between an individual tree and a stand level basal area growth model that accounts for the correlation between trees within a plot by using seemingly unrelated regression (SUR) to estimate the restri...

2003
Gary Koop Dale J. Poirier

This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components. The approach treats the points on each nonparametric regression line as unknown parameters and uses a prior on the degree of smoothness of each line to ensure ...

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