Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Cem Kadilar"'
Autor:
Ceren Unal, Cem Kadilar
Publikováno v:
Journal of Taibah University for Science, Vol 16, Iss 1, Pp 111-119 (2022)
Using the information in x, we consider a new estimator that uses an exponential function to estimate the unknown population mean of y in the case of non-responding units. These cases are divided into two categories as Case I and Case II. In Case I,
Externí odkaz:
https://doaj.org/article/9a5585d7dccc42e1a5ffa298b54b959e
Autor:
Tolga Zaman, Cem Kadilar
Publikováno v:
AIMS Mathematics, Vol 6, Iss 5, Pp 4265-4279 (2021)
In this study, we propose exponential ratio estimators in the stratified two-phase sampling utilizing an auxiliary attribute. The expressions for the mean squared error of these exponential-type estimators under two different cases are derived and th
Externí odkaz:
https://doaj.org/article/98dd6e4c24904c1cb4559518c5469f6f
Publikováno v:
PLoS ONE, Vol 17, Iss 12, p e0278868 (2022)
In this article, a new robust ratio type estimator using the Uk's redescending M-estimator is proposed for the estimation of the finite population mean in the simple random sampling (SRS) when there are outliers in the dataset. The mean square error
Externí odkaz:
https://doaj.org/article/d7b0cbfe8a7a4d5faea000b8cb0cf3e3
Autor:
Ceren Unal, Cem Kadilar
Publikováno v:
Journal of Mathematical and Fundamental Sciences, Vol 53, Iss 1 (2021)
We propose families of estimators for the population mean using an exponential function in case of non-response. This situation is examined under two cases, Case I and II. The bias, MSE and minimum MSE are separately obtained for both cases. We compa
Externí odkaz:
https://doaj.org/article/3be294f3f8dd452a80d72f9750a55566
Autor:
SUBHASH KUMAR YADAV, CEM KADILAR
Publikováno v:
Revista Colombiana de Estadística, Vol 36, Iss 1, Pp 145-152 (2013)
noindent This article considers the problem of estimating the population variance using auxiliary information. An improved version of Singhs exponential type ratio estimator has been proposed and its properties have been studied under large sample ap
Externí odkaz:
https://doaj.org/article/59010d2c00754925853acd44ba63830a
Autor:
Yunusa Olufadi, Cem Kadilar
Publikováno v:
Journal of Probability and Statistics, Vol 2014 (2014)
We suggest an estimator using two auxiliary variables for the estimation of the unknown population variance. The bias and the mean square error of the proposed estimator are obtained to the first order of approximations. In addition, the problem is e
Externí odkaz:
https://doaj.org/article/52a7de4a52114503a8906eaa699cccdb
Publikováno v:
Journal of Probability and Statistics, Vol 2011 (2011)
Seasonal Autoregressive Fractionally Integrated Moving Average (SARFIMA) models are used in the analysis of seasonal long memory-dependent time series. Two methods, which are conditional sum of squares (CSS) and two-staged methods introduced by Hoski
Externí odkaz:
https://doaj.org/article/8af49376c2c64b2c9ec434a123f56f70
Autor:
Eda Gizem KOÇYİĞİT, CEM KADILAR
Publikováno v:
Communications in Statistics - Theory and Methods. :1-23
In this study, we introduce a new approach to the mean estimators in ranked set sampling. The amount of information carried by the auxiliary variable is measured with the Shannon entropy method on populations and samples and to use this information i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72f6a02beeafffee78b2783d9f941e55
https://doi.org/10.1080/03610926.2022.2100910
https://doi.org/10.1080/03610926.2022.2100910
Autor:
Ceren Ünal, Cem Kadilar
Publikováno v:
Lobachevskii Journal of Mathematics. 42:3285-3296
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0ab9d5c10c7f1a5ff61e1cb8e92a9be
https://doi.org/10.1134/s1995080222010231
https://doi.org/10.1134/s1995080222010231
Autor:
Cem Kadilar, Eda Gizem Koçyiğit
In this article, we study the situation of observations whose ranks cannot be determined for the auxiliary variable in the Ranked Set Sampling (RSS) method. Therefore, we examine the case of tie information for ratio estimators of the population mean
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34d91e5183f66a1ef217f3bf489e25a2
https://avesis.deu.edu.tr/publication/details/331a99ed-39e5-403a-ae75-93da59efed78/oai
https://avesis.deu.edu.tr/publication/details/331a99ed-39e5-403a-ae75-93da59efed78/oai
