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Journal articles on the topic 'Estimators'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Benkhaled, Abdelkader, Abdenour Hamdaoui, and Mekki Terbeche. "MINIMAX SHRINKAGE ESTIMATORS AND ESTIMATORS DOMINATING THE JAMES-STEIN ESTIMATOR UNDER THE BALANCED LOSS FUNCTION." Eurasian Mathematical Journal 13, no. 2 (2022): 18–36. http://dx.doi.org/10.32523/2077-9879-2022-13-2-18-36.

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Abonazel, Mohamed. "Bias correction methods for dynamic panel data models with fixed effects." International Journal of Applied Mathematical Research 6, no. 2 (2017): 58. http://dx.doi.org/10.14419/ijamr.v6i2.7774.

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This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects, which suggested in econometric literature, such as least squares (LS) and generalized method of moments (GMM). These methods obtain biased estimators for DPD models. The LS estimator is inconsistent when the time dimension (T) is short regardless of the cross-sectional dimension (N). Although consistent estimates can be obtained by GMM procedures, the inconsistent LS estimator has a relatively low variance and hence can lead to an estimator with lower root mean square error after the bias is rem

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Cahalan, Jennifer A., Jason Gasper, and Jennifer Mondragon. "Catch estimation in the federal trawl fisheries off Alaska: a simulation approach to compare the statistical properties of three trip-specific catch estimators." Canadian Journal of Fisheries and Aquatic Sciences 72, no. 7 (2015): 1024–36. http://dx.doi.org/10.1139/cjfas-2014-0347.

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Quantifying catch has been recognized worldwide as a critical component in fisheries management. Assessment of discard is challenging because of the requirement for at-sea observation, which is both logistically difficult and costly to fishery agencies. Statistical estimators using robust sampling methods may yield accurate and imprecise estimates given the variability associated with many at-sea discard species and inability for agencies to obtain high sampling fractions. However, biased estimates occur if an inappropriate estimator is used. Using Alaska trawl fisheries as an example, we inve

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Iqbal, Kanwal, Syed Muhammad Muslim Raza, Tahir Mahmood, and Muhammad Riaz. "Exploring mixture estimators in stratified random sampling." PLOS ONE 19, no. 9 (2024): e0307607. http://dx.doi.org/10.1371/journal.pone.0307607.

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Advancements in sensor technology have brought a revolution in data generation. Therefore, the study variable and several linearly related auxiliary variables are recorded due to cost-effectiveness and ease of recording. These auxiliary variables are commonly observed as quantitative and qualitative (attributes) variables and are jointly used to estimate the study variable’s population mean using a mixture estimator. For this purpose, this work proposes a family of generalized mixture estimators under stratified sampling to increase efficiency under symmetrical and asymmetrical distributions a

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Hamdaoui, Abdenour, Waleed Almutiry, Mekki Terbeche, and Abdelkader Benkhaled. "Comparison of Risk Ratios of Shrinkage Estimators in High Dimensions." Mathematics 10, no. 1 (2021): 52. http://dx.doi.org/10.3390/math10010052.

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In this paper, we analyze the risk ratios of several shrinkage estimators using a balanced loss function. The James–Stein estimator is one of a group of shrinkage estimators that has been proposed in the existing literature. For these estimators, sufficient criteria for minimaxity have been established, and the James–Stein estimator’s minimaxity has been derived. We demonstrate that the James–Stein estimator’s minimaxity is still valid even when the parameter space has infinite dimension. It is shown that the positive-part version of the James–Stein estimator is substantially superior to the J

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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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Audu, A., S. A. Abdulazeez, I. Abubakar, Y. M. Ahijjo, A. Gidado, and M. A. Yunusa. "Modified Classes of Regression-Type Estimators of Population Mean in the Presence of Auxiliary Attribute under Double Sampling Scheme." Nigerian Journal of Basic and Applied Sciences 30, no. 2 (2023): 42–53. http://dx.doi.org/10.4314/njbas.v30i2.6.

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In sample survey, reliable and efficient estimates are often obtained using information from auxiliary variables during estimation and designing stages. However, there are times when the auxiliary information is attribute-based. Some authors have proposed estimators using auxiliary attribute information when the population mean of auxiliary attribute is unknown. However, the estimators are ratio- based estimators which are less efficient when the bi-serial correlation between the study variable and the auxiliary attribute is negative. In this study, regression approach was used to modify estim

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8

Hinrichsen, Richard A. "The accuracy of alternative stochastic growth rate estimates for salmon populations." Canadian Journal of Fisheries and Aquatic Sciences 59, no. 6 (2002): 1014–23. http://dx.doi.org/10.1139/f02-065.

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The accuracies of four alternative estimators of stochastic growth rate for salmon populations are examined using bootstrapping. The first estimator is based on a stochastic Leslie matrix model that uses age-specific spawner counts. The other three estimators use spawner counts with limited age-structure information: a BotsfordBrittnacher model method and two diffusion approximation methods, namely, the least squares approach of Dennis and the robust approach of Holmes. Accuracy of the estimators was quantified using median bias and interquartile ranges of the stochastic growth rate estimates

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9

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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10

M. Elgohary, Mervat, Mohamed R. Abonazel, Nahed M. Helmy, and Abeer R. Azazy. "New robust-ridge estimators for partially linear model." International Journal of Applied Mathematical Research 8, no. 2 (2019): 46. http://dx.doi.org/10.14419/ijamr.v8i2.29932.

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This paper considers the partially linear model when the explanatory variables are highly correlated as well as the dataset contains outliers. We propose new robust biased estimators for this model under these conditions. The proposed estimators combine least trimmed squares and ridge estimations, based on the spline partial residuals technique. The performance of the proposed estimators and the Speckman-spline estimator has been examined by a Monte Carlo simulation study. The results indicated that the proposed estimators are more efficient and reliable than the Speckman-spline estimator.

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Schreuder, H. T., H. G. Li, and J. W. Hazard. "PPS and Random Sampling Estimation Using some Regression and Ratio Estimators for Underlying Linear and Curvilinear Models." Forest Science 33, no. 4 (1987): 997–1009. http://dx.doi.org/10.1093/forestscience/33.4.997.

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Abstract Two thousand samples of 30 units were drawn from selected populations for which linear or curvilinear underlying models were postulated between the variable of interest and a covariate. Ratio, and linear and nonlinear regression estimators were compared for bias and relative efficiency of the estimates generated. Regression estimators were found to be the most precise estimators of totals for both random and probability proportional to size (PPS) sampling for a series of tree populations for samples of size 30. The weighted regression estimator in PPS sampling was consistently more ef

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12

Payandeh, Bijan, and Alan R. Ek. "Distance methods and density estimators." Canadian Journal of Forest Research 16, no. 5 (1986): 918–24. http://dx.doi.org/10.1139/x86-163.

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The relative performance of five distance–density estimators was evaluated for the n-tree circular, semicircular, and strip plots on several simulated and natural tree populations. Results indicate that for the n-tree circular plot, the ratio estimator performed very well for most populations examined and for n > 10. The performance of both the maximum likelihood and first moment estimators was affected to a great degree by the spatial pattern of the populations, but they performed satisfactorily for the random and uniform populations and for large n values (i.e., n > 10). Smaltschinski'

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Hassan, Yasir, Muhammad Farooq, Saleha Yasir, and Will Murray. "On Some New Exponential Ratio Estimator of Population Mean in Two Phase Sampling." Sains Malaysiana 52, no. 7 (2023): 2149–62. http://dx.doi.org/10.17576/jsm-2023-5207-20.

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In this paper, we suggest employing the exponential ratio estimator to estimate the mean of the study variable using a two-phase sample strategy with two modified auxiliary variables. Several researchers discussed the properties of the estimators they proposed and discovered that the estimators in their studies were relatively efficient. The estimators previously studied are listed chronologically in the appendix to this paper. In two phase sampling, the estimator's mean square errors and relative efficiencies are calculated using auxiliary variable information. To assess the properties of our

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14

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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15

Zaagan, Abdullah A., Mutum Zico Meetei, Shreyanshu Singh, Rajesh Gupta, Subhash Kumar Yadav, and Mukesh Kumar Verma. "Computing the Population Mean in Stratified Sampling Using an Auxiliary Attribute." Journal of Autonomous Intelligence 7, no. 5 (2024): 1672. http://dx.doi.org/10.32629/jai.v7i5.1672.

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<p>This paper proposes a novel ratio type estimator for the population mean using an auxiliary attribute by implying one auxiliary variable in stratified random sampling using conventional product, exponential, and logarithmic ratio type estimators. The proposed estimator’s MSE and PRE are determined, and PRE is compared with existing estimators. The proposed estimator is more effective than other existing estimators according to theoretical observations, which verifies its numerical examples. The proposed estimator may be used for practical applicability in real life, including agricult

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16

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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Uma, Srivastava, and Kumar Harish. "Estimation of Cut Point in Burr III Sequence under Linear Exponential Loss." International Journal of Innovative Science and Research Technology 7, no. 7 (2022): 501–8. https://doi.org/10.5281/zenodo.6956269.

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This paper estimates the single cut-point in the mean of a Burr III Sequence and its scale parameters before and after the cut point. We introduce a strong estimator of the parameters with the help of Bayesian inference approach, by persevering these estimatorsin the criteria used to estimate the cut-point under Linear Exponential Loss Function. The simulation technique is used compare the estimators. Open-source R software is used in the simulation section. We have taken real data to estimate the parameters of the sequence and then hypothetical observations of the sequence to prove their robu

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18

Khan, Dost Muhammad, Muhammad Ali, Zubair Ahmad, Sadaf Manzoor, and Sundus Hussain. "A New Efficient Redescending M-Estimator for Robust Fitting of Linear Regression Models in the Presence of Outliers." Mathematical Problems in Engineering 2021 (November 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/3090537.

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Robust regression is an important iterative procedure that seeks analyzing data sets that are contaminated with outliers and unusual observations and reducing their impact over regression coefficients. Robust estimation methods have been introduced to deal with the problem of outliers and provide efficient and stable estimates in their presence. Various robust estimators have been developed in the literature to restrict the unbounded influence of the outliers or leverage points on the model estimates. Here, a new redescending M-estimator is proposed using a novel objective function with the pr

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19

Lady, James M., and John R. Skalski. "Estimators of stream residence time of Pacific salmon (Oncorhynchus spp.) based on release-recapture data." Canadian Journal of Fisheries and Aquatic Sciences 55, no. 12 (1998): 2580–87. http://dx.doi.org/10.1139/f98-132.

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The area-under-the-curve method is a widely used method for estimating salmon escapement. The method depends on obtaining an accurate estimate of stream residence time, or stream life. This paper develops two estimators of stream residence time based on release-recapture data: a nonparametric estimator and a parametric estimator. Monte Carlo simulations showed that with an adequate release size and number of sampling occasions, both estimators provide precise estimates of stream residence time. If there is significant right censoring, however, the parametric estimator is significantly less bia

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20

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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Bhat, S. S., and R. Vidya. "Performance of Ridge Estimators Based on Weighted Geometric Mean and Harmonic Mean." Journal of Scientific Research 12, no. 1 (2020): 1–13. http://dx.doi.org/10.3329/jsr.v12i1.40525.

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Ordinary least squares estimator (OLS) becomes unstable if there is a linear dependence between any two predictors. When such situation arises ridge estimator will yield more stable estimates to the regression coefficients than OLS estimator. Here we suggest two modified ridge estimators based on weights, where weights being the first two largest eigen values. We compare their MSE with some of the existing ridge estimators which are defined in the literature. Performance of the suggested estimators is evaluated empirically for a wide range of degree of multicollinearity. Simulation study indic

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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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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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Pal, Surya K., Sagir A. Mahmud, Madan M. Gupta, Housila P. Singh, and Ramkrishna S. Solanki. "Estimation of finite population mean in sample surveys: A new estimator." Journal of Information & Optimization Sciences 44, no. 1 (2023): 157–69. http://dx.doi.org/10.47974/jios-1304.

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Utilizing supplementary information in simple random sampling, this research paper discussed a new method for finding the finite population mean of a predictive variable, and the properties of the suggested method have been investigated. The suggested estimator’s advantages over traditional estimators are demonstrated using theoretical asymptotic techniques and empirical analysis. The recommended estimator outperforms the customary unbiased, ratio, product, and regression estimators, as well as many other known population mean estimators.

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Hone, J. "A Test of the Accuracy of Line and Strip Transect Estimators in Aerial Survey." Wildlife Research 15, no. 5 (1988): 493. http://dx.doi.org/10.1071/wr9880493.

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The accuracy and precision of eight line transect estimators and one strip transect estimator were examined by helicopter aerial survey. Carcasses of feral pigs were counted in an area of treeless floodplain and Eucalyptus woodland. The ratio and Cox's methods, Fourier series, exponential power series, half-normal, exponential polynomial, negative exponential, hermite polynomial and hazard rate estimators gave accurate estimates. Using the survey method described, most estimators were of similar accuracy and precision, but the Fourier series estimator was the most accurate.

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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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Little, Roderick J., and Roger J. Lewis. "Estimands, Estimators, and Estimates." JAMA 326, no. 10 (2021): 967. http://dx.doi.org/10.1001/jama.2021.2886.

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UBA, T. "Hybrid Exponential Type Estimators of Finite Population Mean in Double Sampling." International Journal of Research and Innovation in Applied Science X, no. II (2025): 453–72. https://doi.org/10.51584/ijrias.2025.10020041.

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In this study, two-auxiliary exponential type estimators of finite population mean in Two-phase are proposed. The proposed estimators are extension of (1) estimator finite population mean in SRS to Two-phase sampling. The study investigated efficiency of the proposed estimators by utilizing the ratio of bias to standard error (RBSE) as a proxy to examine confidence limits for estimates. The expressions for the bias and Mean Square Error (MSE) of the estimators were derived. A comprehensive simulation study was carried out to show the efficacy of the estimators as compared to conventional estim

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Mohammadzaheri, Morteza, Mohammadreza Emadi, Mojtaba Ghodsi, Issam M. Bahadur, Musaab Zarog, and Ashraf Saleem. "Development of a Charge Estimator for Piezoelectric Actuators." International Journal of Artificial Intelligence and Machine Learning 10, no. 1 (2020): 31–44. http://dx.doi.org/10.4018/ijaiml.2020010103.

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Charge of a piezoelectric actuator is proportional to its displacement for a wide area of operating. Hence, a charge estimator can estimate displacement for such actuators. However, existing charge estimators take a sizable portion of the excitation voltage, i.e. voltage drop. Digital charge estimators have presented the smallest voltage drop. This article first investigates digital charge estimators and suggests a design guideline to (i) maximise accuracy and (ii) minimise the voltage drop. Digital charge estimators have a sensing resistor; an estimator with a constant resistance is shown to

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O. J, Oladapo, Idowu J. I., Owolabi A. T., Ayinde K., and Adejumo T. J. "A New Ridge Type Estimator in the Logistic Regression Model with Correlated Regressors." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 21 (December 20, 2024): 2528–41. https://doi.org/10.37394/23207.2024.21.208.

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The maximum likelihood (ML) technique is always one of the most widely employed to estimate model parameters in logistic regression models. However, due to the problem of multicollinearity, unstable parameter estimates, and inaccurate variance which affects confidence intervals and hypothesis tests can be achieved. A new two-parameter biased estimator is proposed in this paper to handle multicollinearity in binary logistic regression models. The proposed estimator's properties were determined, and five (5) different types of biasing parameter k (generalized, maximum, median, mid-range, and ari

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Beauducel, André, Christopher Harms, and Norbert Hilger. "Reliability Estimates for Three Factor Score Estimators." International Journal of Statistics and Probability 5, no. 6 (2016): 94. http://dx.doi.org/10.5539/ijsp.v5n6p94.

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Estimates for the reliability of Thurstone’s regression factor score estimator, Bartlett’s factor score estimator, and McDonald’s factor score estimator were proposed. Moreover, conditions for equal reliability of the factor score estimators were presented and the reliability estimates were compared by means of simulation studies. Under conditions inducing unequal reliabilities, reliability estimates were largest for the regression score estimator and lowest for McDonald’s factor score estimator. We provide an R-script and an SPSS-script for the computation of the respective reliability estima

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Hidiroglou, M. A., and V. M. Estevao. "A comparison of small area and calibration estimators via simulation." Statistics in Transition new series 17, no. 1 (2016): 133–54. http://dx.doi.org/10.59170/stattrans-2016-007.

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Domain estimates are typically obtained using calibration estimators that are direct or modified direct. They are direct if they strictly use data within the domain of interest. They are modified direct if they use both data within and outside the domain of interest. An alternative way of producing these estimates is through small area procedures. In this article, we compare the performance of these two approaches via a simulation. The population is generated using a hierarchical model that includes both area effects and unit level random errors. The population is made up of mutually exclusive

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Singh, G. N., and Kumari Priyanka. "Estimation of population mean at current occasion in presence of several varying auxiliary variates in two-occasion successive sampling." Statistics in Transition new series 11, no. 1 (2010): 105–26. http://dx.doi.org/10.59170/stattrans-2010-007.

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The present work intended to emphasize the role of several varying auxiliary variates at both the occasions to improve the precision of estimates at current occasion in two-occasion successive sampling. Two different efficient estimators are proposed and their theoretical properties are examined. Relative comparison of efficiencies of the proposed estimators with the sample mean estimator when there is no matching from previous occasion, and the optimum successive sampling estimator when no auxiliary information is used have been incorporated. Empirical studies are significantly justifying the

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Rawat, Pooja, and Manoj Kumar. "Estimation of Rice Yield at Block Level in Karnal district of Haryana using Remote Sensing Data." INTERNATIONAL JOURNAL OF AGRICULTURAL AND STATISTICAL SCIENCES 21, no. 01 (2025): 115. https://doi.org/10.59467/ijass.2025.21.115.

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Small area estimation is widely acknowledged as a valuable tool for generating reliable estimates when working with limited sample data. Direct yield estimation methods used in general agricultural surveys are effective at national and state levels but face challenges at smaller scales due to limited sample sizes. Over the past decade, there has been a significant surge in demand for precise micro-level statistics. This demand is particularly noticeable at the district, block, and village levels, driven by their extensive and diverse utilization across both public and private sectors. Employin

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Al-Omari, Amer Ibrahim, SidAhmed Benchiha, and Ibrahim M. Almanjahie. "Efficient Estimation of Two-Parameter Xgamma Distribution Parameters Using Ranked Set Sampling Design." Mathematics 10, no. 17 (2022): 3170. http://dx.doi.org/10.3390/math10173170.

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An efficient method such as ranked set sampling is used for estimating the population parameters when the actual observation measurement is expensive and complicated. In this paper, we consider the problem of estimating the two-parameter xgamma (TPXG) distribution parameters under the ranked set sampling as well as the simple random sampling design. Various estimation methods, including the weighted least-square estimator, maximum likelihood estimators, least-square estimator, Cramer–von Mises, the maximum product of spacings estimators, and Anderson–Darling estimators, are considered. A compa

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Attah, Omokova M., and Samuel Olayemi Olanrewaju. "Efficient Combined Estimator for Parameter Estimation of Linear Regression Model with Multicollinearity." Asian Journal of Probability and Statistics 27, no. 5 (2025): 1–11. https://doi.org/10.9734/ajpas/2025/v27i5750.

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The classical linear regression model relies on several key assumptions, including homoscedasticity, normality of errors, independence of observations and the absence of multicollinearity among explanatory variables (Gujarati, 2021), These assumptions are rarely fulfilled in real life situations. Multicollinearity occurs when the assumption of independent explanatory variables is violated (Alreshidi et al., 2025), There are many sources of multicollinearity, some of which are the data collection methods, the constraints placed on the model or having an overdetermined model (Paul, 2006), When m

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Chadyšas, V., and D. Krapavickaitė. "Investigation of Accuracy of a Calibrated Estimator of a Ratio by Modelling." Nonlinear Analysis: Modelling and Control 10, no. 4 (2005): 333–42. http://dx.doi.org/10.15388/na.2005.10.4.15113.

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Estimator of finite population parameter – ratio of totals of two variables – is investigated by modelling in the case of simple random sampling. Traditional estimator of the ratio is compared with the calibrated estimator of the ratio introduced by Plikusas [1]. The Taylor series expansion of the estimators are used for the expressions of approximate biases and approximate variances [2]. Some estimator of bias is introduced in this paper. Using data of artificial population the accuracy of two estimators of the ratio is compared by modelling. Dependence of the estimates of mean square error o

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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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Polacheck, Tom, Ray Hilborn, and Andre E. Punt. "Fitting Surplus Production Models: Comparing Methods and Measuring Uncertainty." Canadian Journal of Fisheries and Aquatic Sciences 50, no. 12 (1993): 2597–607. http://dx.doi.org/10.1139/f93-284.

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Three approaches are commonly used to fit surplus production models to observed data: effort-averaging methods; process-error estimators; and observation-error estimators. We compare these approaches using real and simulated data sets, and conclude that they yield substantially different interpretations of productivity. Effort-averaging methods assume the stock is in equilibrium relative to the recent effort; this assumption is rarely satisfied and usually leads to overestimation of potential yield and optimum effort. Effort-averaging methods will almost always produce what appears to be "reas

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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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Krieg, Sabine, Harm Jan Boonstra, and Marc Smeets. "Small-Area Estimation with Zero-Inflated Data – a Simulation Study." Journal of Official Statistics 32, no. 4 (2016): 963–86. http://dx.doi.org/10.1515/jos-2016-0051.

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Abstract Many target variables in official statistics follow a semicontinuous distribution with a mixture of zeros and continuously distributed positive values. Such variables are called zero inflated. When reliable estimates for subpopulations with small sample sizes are required, model-based small-area estimators can be used, which improve the accuracy of the estimates by borrowing information from other subpopulations. In this article, three small-area estimators are investigated. The first estimator is the EBLUP, which can be considered the most common small-area estimator and is based on

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Shah, M. Younis, and S. E. H. Rizvi. "Improvement for Estimation of Population Mean in Post Stratification using Supplementary Variable." Journal of Scientific Research 67, no. 04 (2023): 47–51. http://dx.doi.org/10.37398/jsr.2023.670408.

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This investigation, considers the estimation for finite population mean utilizing knowledge from a supplementary variable in case of post stratification. We examine the suggested estimator's sample characteristics up to an approximation of order one. The ideal value of the constant in the suggested estimator has been found to have the lowest mean squared error (MSE). The suggested estimator is contrasted with alternative estimators. An empirical illustration verifies the theoretical results. We demonstrate the advantages of the suggested estimator over the competing estimators via an empirical

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Li, H. G., H. T. Schreuder, and C. T. Scott. "Combining estimates that are both in error subject to marginal constraints." Canadian Journal of Forest Research 20, no. 10 (1990): 1675–79. http://dx.doi.org/10.1139/x90-221.

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Outside estimates with measures of reliability can be combined with existing tabular estimates of resource statistics to produce new, more precise estimates. But cell estimates do not sum to the original marginal or overall totals when this is done. A method is given to adjust the unchanged cell values to maintain additivity. Classical and bootstrap variance estimators are given for the n × 2 case of combining a cell proportion with an outside estimate assumed to be binomially distributed under fixed marginal constraints, and for the n × m case of combining a cell proportion with a binomially

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Huitema, Bradley E., and Joseph W. McKean. "Two Reduced-Bias Autocorrelation Estimators: rF1 and rF2." Perceptual and Motor Skills 78, no. 1 (1994): 323–30. http://dx.doi.org/10.2466/pms.1994.78.1.323.

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Among the problems associated with the application of time-series analysis to typical psychological data are difficulties in parameter estimation. For example, estimates of autocorrelation coefficients are known to be biased in the small-sample case. Previous work by the present authors has shown that, in the case of conventional autocorrelation estimators of ρ1 the degree of bias is more severe than is predicted by formulas that are based on large-sample theory. Two new autocorrelation estimators, rF1 and rF2, were proposed; a Monte Carlo experiment was carried out to evaluate the properties

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Newey, Whitney K. "Kernel Estimation of Partial Means and a General Variance Estimator." Econometric Theory 10, no. 2 (1994): 1–21. http://dx.doi.org/10.1017/s0266466600008409.

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Econometric applications of kernel estimators are proliferating, suggesting the need for convenient variance estimates and conditions for asymptotic normality. This paper develops a general “delta-method” variance estimator for functionals of kernel estimators. Also, regularity conditions for asymptotic normality are given, along with a guide to verify them for particular estimators. The general results are applied to partial means, which are averages of kernel estimators over some of their arguments with other arguments held fixed. Partial means have econometric applications, such as consumer

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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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Chandni, Kumari, and Kumar Thakur Ratan. "On Construction of Modified Class of Estimators for Population Variance using Auxiliary Attribute." International Journal of Management and Humanities (IJMH) 4, no. 9 (2020): 109–19. https://doi.org/10.35940/ijmh.I0878.054920.

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In this paper, an improved estimator for population variance has been proposed to improvise the log-type estimators proposed by Kumari et al. (2019). The properties of proposed estimators are derived up to the first order of approximation. The proposed estimatorfound to be betterthan the existing estimatorsin the sense of mean squraed error and percent relative efficiency. A numerical study is included to support the use of the suggested classes of estimators.

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Aladeitan, BENEDICTA, Adewale F. Lukman, Esther Davids, Ebele H. Oranye, and Golam B. M. Kibria. "Unbiased K-L estimator for the linear regression model." F1000Research 10 (August 19, 2021): 832. http://dx.doi.org/10.12688/f1000research.54990.1.

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Background: In the linear regression model, the ordinary least square (OLS) estimator performance drops when multicollinearity is present. According to the Gauss-Markov theorem, the estimator remains unbiased when there is multicollinearity, but the variance of its regression estimates become inflated. Estimators such as the ridge regression estimator and the K-L estimators were adopted as substitutes to the OLS estimator to overcome the problem of multicollinearity in the linear regression model. However, the estimators are biased, though they possess a smaller mean squared error when compare

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Fischer, Christoph, and Joachim Saborowski. "Variance estimation for mean growth from successive double sampling for stratification." Canadian Journal of Forest Research 50, no. 12 (2020): 1405–11. http://dx.doi.org/10.1139/cjfr-2020-0058.

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Double sampling for stratification (2SS) is a sampling design that is widely used for forest inventories. We present the mathematical derivation of two appropriate variance estimators for mean growth from repeated 2SS with updated stratification on each measurement occasion. Both estimators account for substratification based on the transition of sampling units among the strata due to the updated allocation. For the first estimator, sizes of the substrata were estimated from the second-phase sample (sample plots), whereas the respective sizes in the second variance estimator relied on the larg

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Gould, W. R., L. A. Stefanski, and K. H. Pollock. "Use of simulation–extrapolation estimation in catch–effort analyses." Canadian Journal of Fisheries and Aquatic Sciences 56, no. 7 (1999): 1234–40. http://dx.doi.org/10.1139/f99-052.

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All catch-effort estimation methods implicitly assume catch and effort are known quantities, whereas in many cases, they have been estimated and are subject to error. We evaluate the application of a simulation-based estimation procedure for measurement error models (J.R. Cook and L.A. Stefanski. 1994. J. Am. Stat. Assoc. 89: 1314-1328) in catch-effort studies. The technique involves a simulation component and an extrapolation step, hence the name SIMEX estimation. We describe SIMEX estimation in general terms and illustrate its use with applications to real and simulated catch and effort data

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