Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Ilias, Kevork"'
Publikováno v:
European Journal of Operational Research. 261:1125-1140
Our paper by adopting the latest advances on the probabilistic characterization of directional distance functions as has been introduced by Daraio and Simar (2014), develops a Malmquist productivity index and presents its main decompositions. Specifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93720c28407e773eae02a8055ad35ca7
https://doi.org/10.1016/j.ejor.2017.03.012
https://doi.org/10.1016/j.ejor.2017.03.012
Autor:
Ilias Kevork, George Halkos
Publikováno v:
Applied Economics Letters. 14:191-195
This study, using a certain simulation strategy, for the exact maximum likelihood estimator of θ from the MA(1), estimates appropriate percentiles, together with their standard errors, offering a new set of critical values for testing in finite samp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61ce0f87997e8240d80b6578117910af
https://doi.org/10.1080/13504850500426202
https://doi.org/10.1080/13504850500426202
Autor:
Ilias Kevork, George Halkos
Publikováno v:
Applied Economics Letters. 13:789-793
Although unit root tests have made a great contribution in time series econometrics, their major disadvantage is the low powers they attain on certain occasions, as for the case of the stationary AR(1), when φis close to one. In this study, consider
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c03737229d87129283e07529698a8f09
https://doi.org/10.1080/13504850500407491
https://doi.org/10.1080/13504850500407491
Autor:
Ilias Kevork, George E. Halkos Asst.
Publikováno v:
Journal of Applied Statistics. 32:45-60
In this paper we evaluate the performance of three methods for testing the existence of a unit root in a time series, when the models under consideration in the null hypothesis do not display autocorrelation in the error term. In such cases, simple v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ac47d831d490c596db119bf8fac56b3
https://doi.org/10.1080/0266476052000330286
https://doi.org/10.1080/0266476052000330286
Autor:
George Halkos, Ilias Kevork
Publikováno v:
International Transactions in Operational Research.
Three estimation policies for the optimal order quantity of the classical newsvendor model under exponential demand are evaluated in the current paper. According to the principle of the first estimation policy, the corresponding estimator is obtained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6393308949bbac904d13faeeef5893a5
https://doi.org/10.1111/itor.12036
https://doi.org/10.1111/itor.12036
Publikováno v:
IMA Journal of Management Mathematics. :dpw010
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a863095d10b77dc0d1feaa3b45d01409
https://doi.org/10.1093/imaman/dpw010
https://doi.org/10.1093/imaman/dpw010
Autor:
Ilias Kevork, George Halkos
Publikováno v:
Applied Economics
Showing a dual relationship between ARIMA (0,2,1) with parameter θ=-1 and the random walk, a new alternative hypothesis in the form of ARIMA (0,2,1) is established in this paper for evaluating unit root tests. The power of four methods of testing fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2efbe7d879f79ecc5f5f3bfcb1e61a60
http://www.ssoar.info/ssoar/handle/document/24028
http://www.ssoar.info/ssoar/handle/document/24028
Autor:
George, Halkos, Ilias, Kevork
In this study we show that a random walk model with drift and first order autocorrelated errors, AR(1), behaves like an ARIMA(1,1,0). The last one is extracted from the unrestricted model of the Augmented Dickey Fuller test using as an explanatory va
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::6ffd87b1b3f021f4c0d518442d44b667
https://mpra.ub.uni-muenchen.de/33312/1/MPRA_paper_33312.pdf
https://mpra.ub.uni-muenchen.de/33312/1/MPRA_paper_33312.pdf
Autor:
George, Halkos, Ilias, Kevork
In this study, using Monte Carlo simulations, we evaluate three alternative methods for constructing confidence intervals for the population mean in the case of a stationary first order autoregressive process, AR(1), with parameter . Differentiating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::b47d37c5f612e8d3f60e16923183ed3a
https://mpra.ub.uni-muenchen.de/33324/1/MPRA_paper_33324.pdf
https://mpra.ub.uni-muenchen.de/33324/1/MPRA_paper_33324.pdf