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Artykuły w czasopismach na temat „Ratio type estimator”

Autor: Grafiati

Data publikacji: 8 września 2023

Data aktualizacji: 25 lipca 2025

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1

YADAV, SUBHASH KUMAR, DIKSHA ARYA, TUBA KOC, and TOLGA ZAMAN. "AN EFFICIENT FAMILY OF RATIO TYPE ESTIMATORS FOR SIMPLE RANDOM SAMPLING." Journal of Science and Arts 24, no. 1 (2024): 69–94. http://dx.doi.org/10.46939/j.sci.arts-24.1-a07.

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The study provides an enhanced estimation of the population mean using known information on an auxiliary variable. An enhanced class of estimators is suggested for the same. The proposed estimator's bias and mean squared error (MSE) are calculated up to the first order of approximation. The optimum values of the characterizing constants are obtained by minimizing the MSE of the proposed estimator. The minimum MSE and the bias values are achieved by optimising the characterizing scalar. The MSE of the proposed estimator has also been compared both conceptually and empirically with the MSEs of c

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2

Sharma, Rubal, and Sangeeta Malik. "Exponential Type Ratio and Product Estimator of Finite Population Mean in Stratified Sampling." Indian Journal Of Science And Technology 17, no. 40 (2024): 4168–76. http://dx.doi.org/10.17485/ijst/v17i40.2237.

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Objective: This article presents an exponential-type ratio and product estimator of the finite population mean within the stratification framework. A common technique in survey sampling is stratification, which divides the population into similar subsets to improve the estimator's accuracy. Methods: This paper tackles the problem of determining the expression for bias and Mean Square Error (MSE) for the population up to the 1st degree of the approximation when stratification is present. Findings: Here it is obtained the optimum value of the modified estimator. The modified estimator is more ef

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3

Shaheen, Nazia, Muhammad Nouman Qureshi, Osama Abdulaziz Alamri, and Muhammad Hanif. "Optimized inferences of finite population mean using robust parameters in systematic sampling." PLOS ONE 18, no. 1 (2023): e0278619. http://dx.doi.org/10.1371/journal.pone.0278619.

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In this article, we have proposed a generalized estimator for mean estimation by combining the ratio and regression methods of estimation in the presence of auxiliary information using systematic sampling. We incorporated some robust parameters of the auxiliary variable to obtain precise estimates of the proposed estimator. The mathematical expressions for bias and mean square error of proposed the estimator are derived under large sample approximation. Many other generalized ratio and product-type estimators are obtained from the proposed estimator using different choices of scalar constants.

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4

Ran, Vijay Kumar Singh, Adebayo Mohammed Abd-Elfatai, Ahmed Audu Ahmed, and Abiola Sanusi Abdulmuahimin. "EFFICIENCY COMPARISON OF RATIO TYPE ESTIMATORS." Continental J. Applied Sciences 8, no. 2 (2013): 34–39. https://doi.org/10.5281/zenodo.2573185.

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The efficiencies of the ratio type estimators have been increased by using linear transformation on auxiliary variable in the literature. Keeping in view, a ratio type estimator of the population mean of variable of interest has been proposed involving unknown weights. Theoretically, its bias and mean square error (mse) have been obtained and compared with other conventional and considered estimators. By this comparison, the conditions that make the proposed estimator more efficient than others have been found. Optimum bias and mean square  error of proposed estimator have  also been

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5

Muhammad, Isah. "Generalized Ratio-Product cum Regression Variance Estimator in Two-Phase Sampling." Central Bank of Nigeria Journal of Applied Statistics 14, no. 2 (2023): 73–101. http://dx.doi.org/10.33429/cjas.14223.4/5.

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This study develops a flexible and efficient generalized ratio-product cum regression-type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived using first order approximation. The theoretical conditions under which the precision and the flexibility of the estimator is better than some classical estimators are also provided. Empirical evidence from five real datasets suggests that the proposed estimator outperforms the classical variance, ratio

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6

Rather, Khalid Ul Islam, Eda Gizem Koçyiğit, Ronald Onyango, and Cem Kadilar. "Improved regression in ratio type estimators based on robust M-estimation." PLOS ONE 17, no. 12 (2022): e0278868. http://dx.doi.org/10.1371/journal.pone.0278868.

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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 (MSE) equation of the proposed estimator is obtained using the first order of approximation and it has been compared with the traditional ratio-type estimators in the literature, robust regression estimators, and other existing redescending M-estimators. A real-life data and simulation study are used to justify the efficiency of the proposed estima

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7

Yadav, Pooja, and Mukesh Kumar. "A new Dual to Difference-cum-Ratio Type Exponential Estimator of Population Mean." INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES 21, no. 01 (2025): 229. https://doi.org/10.59467/ijass.2025.21.229.

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Auxiliary information is frequently used to improve the efficiency of estimators in sampling theory. With the help of auxiliary information, we can increase the estimator's efficiency and accuracy by incorporating an auxiliary variable. Some of the well-known estimators in this category are ratio estimator, product estimator, regression estimator, exponential ratio estimator and exponential product estimator etc. The major portion of the research in sampling theory revolves around to propose efficient estimators. Dual class of estimators is appropriate and performs better at many occasions. In

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8

Subramani, J., and G. Kumarapandiyan. "A Class of Modified Ratio Estimators for Estimation of Population Variance." Journal of Applied Mathematics, Statistics and Informatics 11, no. 1 (2015): 91–114. http://dx.doi.org/10.1515/jamsi-2015-0006.

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Abstract In this paper we have proposed a class of modified ratio type variance estimators for estimation of population variance of the study variable using the known parameters of the auxiliary variable. The bias and mean squared error of the proposed estimators are obtained and also derived the conditions for which the proposed estimators perform better than the traditional ratio type variance estimator and existing modified ratio type variance estimators. Further we have compared the proposed estimators with that of the traditional ratio type variance estimator and existing modified ratio t

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9

Khan, Mursala, and Rajesh Singh. "Estimation of Population Mean in Chain Ratio-Type Estimator under Systematic Sampling." Journal of Probability and Statistics 2015 (2015): 1–5. http://dx.doi.org/10.1155/2015/248374.

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A chain ratio-type estimator is proposed for the estimation of finite population mean under systematic sampling scheme using two auxiliary variables. The mean square error of the proposed estimator is derived up to the first order of approximation and is compared with other relevant existing estimators. To illustrate the performances of the different estimators in comparison with the usual simple estimator, we have taken a real data set from the literature of survey sampling.

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10

Malik, Sachin, and Rajesh Singh. "Some Improved Multivariate-Ratio-Type Estimators Using Geometric and Harmonic Means in Stratified Random Sampling." ISRN Probability and Statistics 2012 (August 26, 2012): 1–7. http://dx.doi.org/10.5402/2012/509186.

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Auxiliary variable is commonly used in survey sampling to improve the precision of estimates. Whenever there is auxiliary information available, we want to utilize it in the method of estimation to obtain the most efficient estimator. In this paper using multiauxiliary information we have proposed estimators based on geometric and harmonic mean. It was also shown that estimators based on harmonic mean and geometric mean are less biased than Olkin (1958) and Singh (1967) estimators under certain conditions. However, the MSE of Olkin (1958) estimator and geometric and harmonic estimators are sam

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11

Bhat, Arshid Ahmad, Manish Sharma, Mohd Younis Shah, and Mehraj Ud Din Bhat. "Generalized Ratio Type Estimator under Adaptive Cluster Sampling." Journal of Scientific Research 67, no. 03 (2023): 46–51. http://dx.doi.org/10.37398/jsr.2023.670307.

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The Adaptive Cluster Sample (ACS) sampling design is employed for the evaluation of scarce, concentrated, vulnerable, and complicated population parameters. Generalized ratio type estimator under ACS has been proposed in this paper. The theoretical formulas of the suggested estimator's mean square error is generated up to first order. Using the simulated x- and y-values from Chutiman and Kumphon (2008), the proposed estimator's effectiveness is empirically evaluated with certain known ratio and ACS estimators. Furthermore, the empirical optimum values of p and q are determined. The results ind

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12

Olasunkanmi Muili, Jamiu, and A. Audu. "Estimation of Finite Population Mean of Median Based Using Power Transformation." Oriental Journal of Physical Sciences 6, no. 1-2 (2022): 26–31. http://dx.doi.org/10.13005/ojps06.01-02.05.

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This paper deals with the assessment of finite population mean. An estimator is suggested for estimation of finite population mean of study variable. The purpose of this study is to evolve a ratio-type estimator to enhance the proficiency of the existing estimators considered in the study in sample random sampling without replacement using information of auxiliary variable. Expressions of the bias and mean square error (MSE) of the proposed estimator was derived by Taylor series method. The efficiency conditions under which the proposed ratio-type estimator is better than sample mean, ratio es

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13

Isah, Muhammad Yahaya Zakari Mannir Abdu Rufai Iliyasu Mujtaba Suleiman Samaila Manzo Ali Muhammad and Adamu Zakar Adamu. "Enhanced Ratio-Type Estimator for Finite Population Mean using Auxiliary Variable in Simple Random Sampling." NIPES Journal of Science and Technology Research 5, no. 1 (2023): 242–52. https://doi.org/10.5281/zenodo.7745091.

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<em>In this paper, a ratio-type estimator of finite population mean in simple random sampling without replacement by using information on an auxiliary variable has been proposed. The proposed estimator was obtained by using the strategy of power transformation and incorporated the unknown weight (</em><em>). The objective of this study is to develop a new ratio estimator that provide better precision of estimation of population mean. The properties such as bias and mean square error (MSE) of the proposed estimator are derived and tested using four real data sets. The results of the empirical s

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14

Subzar, Mir, T. A. Raja, Manish Kumar, Sweta Singh, and S. Maqbool. "Robust Ratio Type Estimator as an Alternative to Regression Estimator for Population Mean Estimation in SRSWOR." INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES 21, no. 01 (2025): 271. https://doi.org/10.59467/ijass.2025.21.271.

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In this study, we have proposed ratio estimator, which is an alternative to regression estimator for estimating finite population mean while obtaining their optimal conditions in simple random sampling using Non-conventional measures of dispersion as an auxiliary variable (U), which has strong correlation with study variable (T). However, these proposed estimators are robust estimators on using Huber M estimation technique instead of using OLS technique. Also, we have made analytical as well as Numerical comparison to demonstrate the efficacy of proposed estimators over the existing ones. In t

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15

Bhushan, Shashi, Anoop Kumar, Amer Ibrahim Al-Omari, and Ghadah A. Alomani. "Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators." Mathematics 11, no. 9 (2023): 2125. http://dx.doi.org/10.3390/math11092125.

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This article examines the issue of population mean estimation utilizing past and present data in the form of an exponentially weighted moving average (EWMA) statistic under simple random sampling (SRS). We suggest memory-type logarithmic estimators and derive their properties, such as mean-square error (MSE) and bias up to a first-order approximation. Using the EWMA statistic, the conventional and novel memory-type estimators are compared. Real and artificial populations are used as examples to illustrate the theoretical findings. According to the empirical findings, memory-type logarithmic es

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16

Nikita, Malik Sangeeta, and Sumiti. "A New Ratio and Product Type Estimator for Mean Under Stratified Random Sampling." Indian Journal of Science and Technology 16, no. 48 (2023): 4703–9. https://doi.org/10.17485/IJST/v16i48.2441.

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Abstract <strong>Objectives:</strong> The present study deals with the formation of a modified ratio and product type estimator for estimating finite population mean using auxiliary variables under stratified random sampling. <strong>Methods:</strong> The expression for the bias and mean square error (MSE) of the suggested estimator was computed upto the first degree of approximation by using the ratio and product method of estimation. We used the data of Area and Production of Horticulture Crops, India obtained from the official website of National horticulture board. The anoth

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17

Olufadi, Yunusa, and Cem Kadilar. "A Study on the Chain Ratio-Type Estimator of Finite Population Variance." Journal of Probability and Statistics 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/723982.

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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 extended to two-phase sampling scheme. After theoretical comparisons, as an illustration, a numerical comparison is carried out to examine the performance of the suggested estimator with several estimators.

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18

Sheela, Misra1 Badal Kumar*2 S.K.Yadav3 D.K.Yadav4 &. A.K.Shukla5. "AN IMPROVED RATIO TYPE PREDICTIVE ESTIMATOR FOR ESTIMATING FINITE POPULATION MEAN USING AUXILIARY INFORMATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 6 (2017): 524–30. https://doi.org/10.5281/zenodo.817934.

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In the present article, motivated by Jeelani et al. (2013), we have made an attempt to develop an improved ratio type estimator of population mean using predictive method of estimation by using linear combination of coefficient of skewness and the quartile deviation of auxiliary variable. The mathematical expressions for the bias and mean squared error (MSE) of the proposed estimator up to the first order approximation have been derived. Theoretical efficiency comparison of proposed estimator with the usual ratio estimator, usual product estimator, and Singh et al. (2014) estimators is also ma

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19

K, Oguagbaka, S., Okoli, O. C, and Aronu, C. O. "Ratio estimator for double sampling procedure with non-response: An empirical study." International Journal of Basic and Applied Science 12, no. 4 (2024): 148–58. http://dx.doi.org/10.35335/ijobas.v12i4.281.

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This study proposes a ratio-type estimator for population mean estimation using auxiliary variables with double sampling in the presence of non-response. The study provides expressions for the constant, bias, and mean square errors (MSE) of the proposed estimator and compares it with ten existing estimators. The study employed the secondary source of data collection to evaluate the efficiency of the proposed and existing estimators by analyzing five natural populations from three different sources. The performance of ten (10) estimators was considered in this study. The findings suggest that t

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20

Gupta, Ruchi, and Sangeeta Malik. "Study on New Ratio and Product Type Estimators for Population Mean Under Ranked Set Sampling." Indian Journal Of Science And Technology 18, no. 4 (2025): 297–303. https://doi.org/10.17485/ijst/v18i4.2367.

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Objectives: The study deals with the concept of Ranked Set Sampling (RSS) as an effective measure to find out the mean of the population when a sample of small size can be found without measuring or with other methods like ranking. The primary goal of this study is to investigate how well the proposed estimators perform compared to existing estimators. Methods: This study has introduced new ratio and product estimators to see the population mean under ranked set sampling and compare them with the existing ones in terms of Mean Square Error (MSE) and efficiency. Findings: The optimum value of t

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21

RATHER, KHALID UL ISLAM, M. IQBAL JEELANI, and AFSHAN TABASSUM. "OPTIMUM SEPARATE RATIO -TYPE EXPONENTIAL ESTIMATOR FOR COMPUTATION OF POPULATION MEAN IN STRATIFIED RANDOM SAMPLING." Journal of Science and Arts 22, no. 2 (2022): 331–42. http://dx.doi.org/10.46939/j.sci.arts-22.2-a07.

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In this manuscript, we study the problem of separate type exponential ratio estimator for estimation of population mean with their properties. The MSE and Bias up to the first degree of approximation for the suggested estimator are computed. The suggested estimator is proven to be more efficient than estimators mentioned in the literature under stratified random technique. An empirical investigation was done to assess the suggested estimator. Also, the percent relative efficiency is to be remarkable for the proposed estimator.

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22

Yunusa, Mojeed Abiodun, Ahmed Audu, and Awwal Adejumobi. "Logarithmic-Product-Cum-Ratio Type Estimator for Estimating Finite Population Coefficient of Variation." Oriental Journal of Physical Sciences 7, no. 2 (2023): 82–87. http://dx.doi.org/10.13005/ojps07.02.05.

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Estimation of population parameters have been a challenging aspect in sample survey for sometimes and many efforts have been made to enhance the exactness of the parameters of these estimators. We suggested the logarithmic-product-cum-ratio type estimator. Expression of the MSE of the intended estimator originated using the Taylor series technique. A numerical illustration was conducted and the results revealed that the modified work is ameliorated than sample means with other estimators observed.

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23

Rubal, Sharma, and Malik Sangeeta. "Exponential Type Ratio and Product Estimator of Finite Population Mean in Stratified Sampling." Indian Journal of Science and Technology 17, no. 40 (2024): 4168–76. https://doi.org/10.17485/IJST/v17i40.2237.

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Abstract <strong>Objective:</strong> This article presents an exponential-type ratio and product estimator of the finite population mean within the stratification framework. A common technique in survey sampling is stratification, which divides the population into similar subsets to improve the estimator's accuracy. <strong>Methods:</strong> This paper tackles the problem of determining the expression for bias and Mean Square Error (MSE) for the population up to the 1st degree of the approximation when stratification is present.<strong> Findings:</strong> Here it is ob

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24

Rabiu, Adam, Abubakar Yahaya, and Muhammad Abdulkarim. "MODIFICATION OF SEPARATE RATIO TYPE EXPONENTIAL ESTIMATOR: A POST-STRATIFICATION APPROACH." FUDMA JOURNAL OF SCIENCES 5, no. 2 (2021): 404–12. http://dx.doi.org/10.33003/fjs-2021-0502-629.

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In this research, modification of separate ratio type exponential estimator introduced in an earlier study is proposed. Expressions for the bias and mean square error (MSE) of the proposed estimator up to first degree of approximation are derived. The optimum value of the constant which minimize the MSE of the suggested estimator is also obtained. In the same vein, efficiency comparisons between the proposed estimator and some related existing ones under the case of post-stratification is conducted. Empirical studies have been conducted to demonstrate the efficiencies of the suggested estimato

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25

Swain, A. K. P. C., and Manjula Das. "Some classes of modified ratio type estimators in sample surveys." Statistics in Transition new series 16, no. 1 (2015): 37–52. http://dx.doi.org/10.59170/stattrans-2015-002.

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In this paper some classes of modified ratio type estimators with additive and multiplicative adjustments made to the simple mean per unit estimator and classical ratio estimator are suggested to obtain more efficient ratio type estimators compared to the classical one. Their biases and mean square errors are obtained and compared with first order approximations.

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26

Mittal, Alisha, and Manoj Kumar. "Two new estimators of finite population variance under random non-response: An application." Model Assisted Statistics and Applications 18, no. 1 (2023): 73–84. http://dx.doi.org/10.3233/mas-221361.

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In this paper, an attempt has been made to study the estimation of finite population variance in simple random sampling without replacement (SRSWOR) in presence of non-response by proposing two estimators. The two estimators (dual to ratio and ratio cum dual to ratio type) have been proposed on the basis of availability and non-availability of auxiliary information. The properties such as bias and mean square error of the proposed estimators have also been studied up to first order of approximation. The proposed estimators are compared with some existing estimators and are also mutually compar

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27

Tiwari, Neeraj, Jharna Banerjie, Girish Chandra, and Shailja Bhari. "Ratio Type Estimator for Balanced Sampling Plan excluding Adjacent Units." International Journal of Statistical Sciences 24, no. 1 (2024): 103–14. http://dx.doi.org/10.3329/ijss.v24i1.72028.

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The study variables are usually correlated with the auxiliary variables and therefore their correlation could easily be computed. In this paper, the correlation coefficient is used for the estimation procedure, and therefore, we proposed a Horvitz-Thompson ratio-type estimator using correlation coefficient for Balanced Sampling plan excluding Adjacent units (BSA plan). It has been illustrated theoretically and empirically that the proposed Horvitz-Thompson ratio-type estimator is more precise than the Horvitz-Thompson estimator based on BSA plan. The proposed estimator provides an opportunity

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Beevi, Nazeema T., and C. Chandran. "EFFICIENT FAMILY OF RATIO-TYPE ESTIMATORS FOR MEAN ESTIMATION IN SUCCESSIVE SAMPLING ON TWO OCCASIONS USING AUXILIARY INFORMATION." Statistics in Transition new series 18, no. 2 (2017): 227–45. http://dx.doi.org/10.59170/stattrans-2017-012.

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In this paper, we proposed an efficient family of ratio-type estimators using one auxiliary variable for the estimation of the current population mean under successive sampling scheme. This family of estimators have been studied by Ray and Sahai (1980) under simple random sampling using one auxiliary variable for estimation of the population mean. Using these estimators in successive sampling, the expression for bias and mean squared error of the proposed estimators are obtained up to the first order of approximation. Usual ratio estimator is identified as a particular case of the suggested es

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Kamal, Asifa, Nimra Amir, and Huma Dastagir. "Some Exponential Type Predictive Estimators of Finite Population Mean in Two-Phase Sampling." STATISTICS, COMPUTING AND INTERDISCIPLINARY RESEARCH 2, no. 1 (2020): 51–57. http://dx.doi.org/10.52700/scir.v2i1.10.

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This study is designed for predictive estimation of finite population mean in two phase sampling using two auxiliary variables. Two phase exponential ratio type estimator and exponential chain ratio type estimator are proposed under predictive approach suggested by Bahl & Tuteja (1991). The expressions of bias and mean square error of both suggested estimators have been carried out for theoretical comparison. The numerical study on real life data sets as well as simulation study has been conducted to examine the performance of suggested estimators. Finally, it is demonstrated that the sugg

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Muhammad, Isah, Yahaya Zakari, and Ahmed Audu. "An Alternative Class of Ratio-Regression-Type Estimator under Two-Phase Sampling Scheme." Central Bank of Nigeria Journal of Applied Statistics 12, no. 2 (2022): 1–26. http://dx.doi.org/10.33429/cjas.12221.1/5.

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In this study, a new exponential ratio-regression estimator is developed using an auxiliary variable for estimating the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed estimator are derived and compared with some of the estimators in extant literature. Thus, the conditions under which the proposed estimator is better than some existing estimators are provided. Empirically, using four real datasets and simulation study, the proposed estimator performs better than the classical ratio, classical regression, exponential ratio, and expo

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Muhammad, Isah, Yahaya Zakari, and Ahmed Audu. "An Alternative Class of Ratio-Regression-Type Estimator under Two-Phase Sampling Scheme." Central Bank of Nigeria Journal of Applied Statistics 12, no. 2 (2022): 1–26. http://dx.doi.org/10.33429/cjas.12221.1/5.

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In this study, a new exponential ratio-regression estimator is developed using an auxiliary variable for estimating the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed estimator are derived and compared with some of the estimators in extant literature. Thus, the conditions under which the proposed estimator is better than some existing estimators are provided. Empirically, using four real datasets and simulation study, the proposed estimator performs better than the classical ratio, classical regression, exponential ratio, and expo

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Muhammad, Isah, Yahaya Zakari, and Ahmed Audu. "An Alternative Class of Ratio-Regression-Type Estimator under Two-Phase Sampling Scheme." Central Bank of Nigeria Journal of Applied Statistics 12, no. 2 (2022): 1–26. http://dx.doi.org/10.33429/cjas.12221.1/5.

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In this study, a new exponential ratio-regression estimator is developed using an auxiliary variable for estimating the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed estimator are derived and compared with some of the estimators in extant literature. Thus, the conditions under which the proposed estimator is better than some existing estimators are provided. Empirically, using four real datasets and simulation study, the proposed estimator performs better than the classical ratio, classical regression, exponential ratio, and expo

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PANDEY, RANJITA, and KALPANA YADAV. "Population variance estimation using factor type imputation method." Statistics in Transition new series 18, no. 3 (2017): 375–92. http://dx.doi.org/10.59170/stattrans-2017-019.

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We propose a variance estimator based on factor type imputation in the presence of non-response. Properties of the proposed classes of estimators are studied and their optimality conditions are derived. The proposed classes of factor type ratio estimators are shown to be more efficient than some of the existing estimators, namely, the usual unbiased estimator of variance, ratio-type, dual to ratio type and ratio cum dual to ratio estimators. Their performances are assessed on the basis of relative efficiencies. Findings are illustrated based on a simulated and real data set.

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Yunusa, Mojeed Abiodun, Jamiu Olasunkanmi Muili, Ahmed Audu, and Ran Vijay Kumar Singh. "A Sine Type Median Based Estimator for the Estimation of Population Mean." Oriental Journal of Physical Sciences 8, no. 1 (2023): 21–26. http://dx.doi.org/10.13005/ojps08.01.05.

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In the literature, there are numerous estimators for estimating population means when auxiliary information is provided. Subramani suggested ratio median based estimator when the median of the study variable is available and the regression estimator was shown to be significantly less efficient than the estimator. In this research, we suggested an estimator for the population mean of the studied variable based on a sine type median. Using Taylor series expansion, the bias and mean square error of the estimator were obtained up to the first order of approximation. The condition under which the p

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Mittal, Alisha, and Manoj Kumar. "GENERALISED EXPONENTIAL RATIO-TYPE ESTIMATOR FOR FINITE POPULATION VARIANCE UNDER RANDOM NON-RESPONSE." International Journal of Advanced Research 9, no. 01 (2021): 589–96. http://dx.doi.org/10.21474/ijar01/12332.

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In this research paper an effort has been made for the estimation of population variance of the study variable by using information on certain known parameters of the auxiliary variable under non-response for scheme I and II given by Singh and Joarder (1998). Generalized exponential ratio-type estimator has been proposed and their properties have been studied under non response techniques and conditions were found when the family of proposed estimators identified by using different choices for (P, Q) performed better than the usual unbiased estimator. It was also observed that for different va

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Agbebia, C. S., and E. I. Enang. "Calibration Approach Ratio Estimators of Population Median in Stratified Random Sampling Design." Asian Journal of Probability and Statistics 21, no. 4 (2023): 64–77. http://dx.doi.org/10.9734/ajpas/2023/v21i4472.

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Median as a measure of location gives a more robust estimate than the mean when dealing with heavy tailed or skewed distributions. It can also be used in cases of qualitative variables and open end intervals. Calibration, an approach that adjusts the original design weight by incorporating auxiliary information is employed using the chi square distance measure on a ratio median estimator under stratified random sampling to propose some estimators of population median. These proposed estimators are: the regression and ratio-type calibrated estimators with one constraint and the regression and r

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37

Suleiman, Haruna, Yisa Yakubu, Usman Abubakar, Zibairu Abdullahi Umar, and Usman Yahaya Baba. "On the Efficiency of Generalized Version Exponential Ratio Cum to Dual-Ratio Cum Type Estimator Via Robust Measure." Asian Research Journal of Mathematics 21, no. 3 (2025): 1–18. https://doi.org/10.9734/arjom/2025/v21i3896.

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Ratio-cum to Dual ratio-cum type of population mean is addressed under known influence of auxiliary variable which is designed to be resistant to the effects of outliers Datasets. The expression for the bias, mse and mmse of the proposed estimator is studied and optimality is tested. Theoretical efficiency comparison of the proposed estimator over some existing estimators of the same characteristics reviews are established. The performance is evaluated used metrics mention in support of theoretical results, however considered on two Natural and simulated datasets using R script. Results indica

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38

Shukla, Diwakar, Sharad Pathak, and Narendra Singh Thakur. "Estimation of population mean using two auxiliary sources in sample surveys." Statistics in Transition new series 13, no. 1 (2013): 21–36. http://dx.doi.org/10.59170/stattrans-2012-002.

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This paper proposes families for estimation of population mean of the main variable under study using the information on two different auxiliary variables under simple random sampling without replacement (SRSWOR) scheme. Three different classes of estimators are constructed, examined with a complete study with other existing estimators. The expression for bias and mean squared error of the proposed families are obtained up to first order of approximation. Usual ratio estimator, product estimator, dual to ratio estimator, ratio-cum-product type estimator and many more estimators are identified

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39

Apantaku, F. S., O. M. Olayiwola, A. I. Adewole, and A. A. Alagbe. "A Generalized Family of Ratio-Product Exponential Type Estimator Using Power Transformation." Dutse Journal of Pure and Applied Sciences 9, no. 4a (2024): 81–93. http://dx.doi.org/10.4314/dujopas.v9i4a.7.

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Usage of Auxiliary information has been widely addressed in literature with a view of enhancing the precision of the estimators of population parameters. this paper reviewed research works of some exponential and ratio type estimators for estimating the population parameters using the population mean of an auxiliary variable. In this research, a generalized family of ratio-product type estimator of population mean as well as the coefficient of kurtosis of two auxiliary variables x and z under stratified random sampling has been proposed using power transformation and exponential techniques. Th

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40

Sharma, Rubal, and Sangeeta Malik. "An Efficient Exponential Ratio and Product Type Estimator in Post-Stratification." International Journal of Science and Research (IJSR) 13, no. 6 (2024): 190–94. http://dx.doi.org/10.21275/sr24601211100.

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41

Sahoo, Nirupama, and Sananda Kumar Jhankar. "Improved Ratio-type Exponential Estimator for Estimating Population Mean in Ranked Set Sampling." Journal of the Indian Society of Agricultural Statistics 78, no. 2 (2024): 135–41. http://dx.doi.org/10.56093/jisas.v78i2.7.

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In this paper we propose a ratio-type exponential estimator for estimating population mean of the study variable under Ranked set sampling when auxiliary information is known. The bias and Mean square error of the proposed estimator has been derived up to the first degree of approximation. A simulation study has been carried out to judge the performance of the newly proposed estimator along with existing estimators. It is obtained that the proposed estimator is more efficient as compared to the competing estimators.

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42

Ijaz, Muhammad, Syed Muhammad Asim, Atta ullah, and Ibrahim Mahariq. "Flexible Robust Regression-Ratio Type Estimators and Its Applications." Mathematical Problems in Engineering 2022 (September 28, 2022): 1–6. http://dx.doi.org/10.1155/2022/8977392.

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In real-world situations, the data set under examination may contain uncommon noisy measurements that unreasonably affect the data’s outcome and produce incorrect model estimates. Practitioners employed robust-type estimators to reduce the weight of the noisy measurements in a data set in such a scenario. Using auxiliary information that will produce reliable estimates, we have looked at a few flexible robust-type estimators in this study. In order to estimate the population mean, this study presents unique flexible robust regression type ratio estimators that take into account the data from t

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43

Sharma, Rubal, Sangeeta Malik, and Ruchi Gupta. "Developing Robust Exponential Ratio and Product Estimators for Post-Stratification: Addressing Non-Response and Enhancing Accuracy Through Double Sampling." American Journal of Mechanics and Applications 12, no. 1 (2025): 1–10. https://doi.org/10.11648/j.ajma.20251201.11.

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A key survey sampling technique, post stratification, involves dividing a population that is diverse into strata with rather homogeneous members in order to improve population estimates. Modern large scale surveys often suffer from non-response, and these too will yield biased results. According to this paper, a new estimator which combines non response adjustment and double sampling techniques to improve the accuracy of product type and exponential ratio estimators is introduced. The proposed estimator has lower bias and mean squared error (MSE) on population mean estimators when response rat

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44

Onyango, Ronald, Brian Oduor, and Francis Odundo. "Mean Estimation of a Sensitive Variable under Nonresponse Using Three-Stage RRT Model in Stratified Two-Phase Sampling." Journal of Probability and Statistics 2022 (April 22, 2022): 1–14. http://dx.doi.org/10.1155/2022/4530120.

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The present study addresses the problems of mean estimation and nonresponse under the three-stage RRT model. Auxiliary information on an attribute and variable is used to propose a generalized class of exponential ratio-type estimators. Expressions for the bias, mean squared error, and minimum mean squared error for the proposed estimator are derived up to the first degree of approximation. The efficiency of the proposed estimator is studied theoretically and numerically using two real datasets. From the numerical analysis, the proposed generalized class of exponential ratio-type estimators ou

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45

Swain, A. K. P. C. "On efficient difference type estimators." Statistics in Transition new series 11, no. 3 (2010): 555–62. http://dx.doi.org/10.59170/stattrans-2010-031.

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This paper considers a more efficient difference type estimator in a finite population set-up. Ratio type and regression type estimators are derived as special cases. Further efficiencies of these estimators are compared with classical ratio and regression estimators. Numerical illustrations are provided to compare efficiencies of different competitive estimators.

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Magnussen, Steen, and Thomas Nord-Larsen. "A Jackknife Estimator of Variance for a Random Tessellated Stratified Sampling Design." Forest Science 65, no. 5 (2019): 543–47. http://dx.doi.org/10.1093/forsci/fxy070.

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Abstract Semisystematic sampling designs—in which a population area frame is tessellated into cells, and a randomly located sample is taken from each cell—affords random tessellated stratified (RTS) Horvitz–Thompson-type estimators. Forest inventory applications with RTS estimators are rare, possibly because of computational complexities with the estimation of variance. To reduce this challenge, we propose a jackknife estimator of variance for RTS designs. We demonstrate an application with a model-assisted ratio of totals estimator and data from the Danish National Forest Inventory. RTS estim

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47

Rather, K. Ul Islam, M. Iqbal Jeelani, M. Younis Shah, S. E. H. Rizvi, and M. Sharma. "A new ratio type estimator for computation of population mean under post-stratification." Journal of Applied Mathematics, Statistics and Informatics 18, no. 1 (2022): 29–42. http://dx.doi.org/10.2478/jamsi-2022-0003.

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Abstract In this study, the difficulty of estimating the population mean in the situation of post-stratification is discussed. The case of post-stratification is presented for ratio-type exponential estimators of finite population mean. Mean-squared error of the proposed estimator is obtained up to the first degree of approximation. In the instance of post-stratification, the proposed estimator was compared with the existing estimators. An empirical study by using some real data and further, simulation study has been carried out to demonstrate the performance of the proposed estimator.

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48

Sahoo, Nirupama, and Sananda Kumar Jhankar. "A chain ratio-type exponential estimator for population mean in double sampling." Statistics in Transition new series 25, no. 1 (2024): 63–76. http://dx.doi.org/10.59170/stattrans-2024-004.

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In this paper we have proposed an efficient ratio-type exponential estimator for estimating the population mean of the study variable, by incorporating two auxiliary variables in twophase (double) sampling. The bias and the mean square error of the proposed estimator have been obtained up to the first order of approximation. The newly proposed estimator offers more precision in comparison to other competing estimators, theoretically as well as empirically, by considering a known value of some population parameter.

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49

Faweya, Olanrewaju, Esther Ajayi, and Oluwadare Akinyemi. "A New Ratio Type Estimator for Double Sampling with Two Auxiliary Variables." International Journal of Innovative Science and Research Technology 8, no. 2 (2023): 2162–67. https://doi.org/10.5281/zenodo.7743391.

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- In this paper, we propose a new ratio type estimator for double sampling with two auxiliary variables. The expressions for bias and mean square error (MSE) of the proposed estimator have been obtained. Some realistic conditions have been obtained under which the proposed estimator is more efficient than the usual unbiased well-known existing estimators of double sampling using two auxiliary variables for population mean and it was found to be more efficient in many situations.

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Ravendra, Kumar*1 Dharmendra Kumar Yadav2 Prof Sheela Misra3 &. S.K. Yadav4. "ESTIMATING POPULATION MEAN USING KNOWN MEDIAN OF THE STUDY VARIABLE." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 7 (2017): 15–21. https://doi.org/10.5281/zenodo.822944.

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This present paper concerns with the estimation of population mean of the study variable by utilizing the known median of the study variable. A generalized ratio type estimator has been proposed for this purpose. The expressions for the bias and mean squared error of the proposed estimator have been derived up to the first order of approximation. The optimum value of the characterizing scalar has also been obtained. The minimum value of the proposed estimator for this optimum value of the characterizing scalar is obtained. A theoretical efficiency comparison of the proposed estimator has been

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