Model Assisted Statistics and Applications - Volume 16, issue 2

Authors: Lipovetsky, Stan

Article Type: Editorial

DOI: 10.3233/MAS-210520

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 85-86, 2021

Authors: P. Singh, Housila | Patidar, Preeti

Article Type: Research Article

Abstract: This paper suggests a new randomized response model useful for gathering information on quantitative sensitive variable such as drug usage, tax evasion and induced abortions etc. The resultant estimator has been found to more efficient than the estimator of the Saha (2007) under some realistic conditions. We have illustrated results numerically.

Keywords: Bias, variance, scrambled response model, sensitive variable, estimation of mean

DOI: 10.3233/MAS-210521

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 87-95, 2021

Authors: Priyanka, Kumari

Article Type: Research Article

Abstract: The estimation of finite population mean at current occasion in two occasion successive sampling in presence of non-response is investigated using tuned jackknife estimators. Based on the availability of auxiliary information at population level (Info U) and sample level (Info s) and using tuned jackknife technique, estimators have been proposed. Estimator of variance of proposed estimators have also been discussed. Different cases of occurance of non-response have been explored. The estimators are mutually compared. The properties of these estimators are studied via simulation study using natural population.

Keywords: Successive occasions, non-response, tuned jackknife estimator, population mean, variance

DOI: 10.3233/MAS-210522

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 97-108, 2021

Authors: P. Dibal, Nicholas | Dallah, Hamadu

Article Type: Research Article

Abstract: Observations on certain real-life cases include units that are incompatible with other data sets. Values that are extreme in nature do influence estimates obtained by conventional estimators. Robust estimators are therefore necessary for efficient estimation of parameters. This paper uses stratification with simple random sampling without replacement to optimize sample allocation in stratum for efficient parameter estimation as an alternative method of handling highly contaminated samples. Our proposed method stratifies the highly contaminated population into two non-overlapping sub-populations, and stratified samples of sizes 50, 200, and 500 was drawn. We estimate the model parameters form the contaminated sampled data using …ordinary least squares under the proposed method, and using the two high breakdown point estimators; the Least Median of Squares and Least Trimmed Squares. Our findings shows that the proposed method did not perform well for low contamination levels (⩽ 30%) but outperformed Least Median of Squares and Least Trimmed Squares for higher contamination rates (⩾ 40%). This indicates that our proposed method compares well and compete favorably with the two high breakdown point estimators. Show more

Keywords: Stratification, contamination, high breakdown point, ordinary least squares

DOI: 10.3233/MAS-210523

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 109-115, 2021

Authors: Silva, Adilson | Fonseca, Miguel

Article Type: Research Article

Abstract: Through simulations, it was shown that either in balanced “one-way” random designs or in unbalanced “one-way” random designs, Sub-D estimates are in general more accurate than those provided by Anova-based estimators. Moreover, the Sub-D estimates exhibit less dispersion magnitude. Such estimates reveal to be also slightly more accurate than those provide by REML-based estimator, although this latter one presented dispersion with slightly less magnitude, which, indeed, is not bigger than 0.0261. In order to have somehow a robust tool which will allow us to infer over Sub-D’s efficiency in “one-way” random designs, this paper aims to deduce and discuss its …MSE. Show more

Keywords: Variance components, Sub-D, MSE, efficiency

DOI: 10.3233/MAS-210524

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 117-123, 2021

Authors: Kumar, Devendra | Nassar, Mazen | Dey, Sanku | Elshahhat, Ahmed

Article Type: Research Article

Abstract: This article accentuates the estimation of a two-parameter generalized Topp-Leone distribution using dual generalized order statistics (dgos ). In the part of estimation, we obtain maximum likelihood (ML) estimates and approximate confidence intervals of the model parameters using dgos , in particular, based on order statistics and lower record values. The Bayes estimate is derived with respect to a squared error loss function using gamma priors. The highest posterior density credible interval is computed based on the MH algorithm. Furthermore, the explicit expressions for single and product moments of dgos from this distribution are also derived. Based on order …statistics and lower records, a simulation study is carried out to check the efficiency of these estimators. Two real life data sets, one is for order statistics and another is for lower record values have been analyzed to demonstrate how the proposed methods may work in practice. Show more

Keywords: Generalized Topp-Leone distribution, order statistics, dual generalized order statistics, lower record values

DOI: 10.3233/MAS-210525

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 125-141, 2021

Authors: Moiseev, Nikita A.

Article Type: Research Article

Abstract: The paper presents a fundamental parametric approach to simultaneous forecasting of a vector of functionally dependent random variables. The motivation behind the proposed method is the following: each random variable at interest is forecasted by its own model and then adjusted in accordance with the functional link. The method incorporates the assumption that models’ errors are independent or weekly dependent. Proposed adjustment is explicit and extremely easy-to-use. Not only does it allow adjusting point forecasts, but also it is possible to adjust the expected variance of errors, that is useful for computation of confidence intervals. Conducted thorough simulation and empirical …testing confirms, that proposed method allows to achieve a steady decrease in the mean-squared forecast error for each of predicted variables. Show more

Keywords: Simultaneous prediction, time series, economic indicators, seemingly unrelated regressions, maximum likelihood estimation, linearly dependent random variables

DOI: 10.3233/MAS-210526

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 143-150, 2021

Authors: Mandel, Igor | Mastandrea, Stefano | Rachenkov, Kirill | Shamshurin, Ivan

Article Type: Research Article

Abstract: There are many studies investigating relationship between paintings’ meta information (author, age, etc.) and their prices, however, there is limited research on how people’s aesthetic perception of paintings is related to their prices. To bridge this gap, we designed a website (pollart1000.com ) collecting survey responses on people’s opinions regarding aesthetic values of paintings; survey and data were complemented with price information. Comprehensive statistical analysis of that data is presented, including scoring of the best and worst works, correlations between variables, typology of respondents, and more. The results quantify relationships between aesthetic values and art prices. Particularly, we showed that …aesthetic preference is inclined to figurative and innovational rather than to abstract art and that relations between price and aesthetic values are rather weak except of special cases. Show more

Keywords: Art price models, painting aesthetic value, metrics of aesthetics, statistical analysis of art

DOI: 10.3233/MAS-210527

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 151-162, 2021

Article Type: Review Article

DOI: 10.3233/MAS-210528

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 163-, 2021

Authors: Lipovetsky, Stan

Article Type: Research Article

Abstract: The work describes developments in the multiple regression performed for building models resistant to multicollinearity, having meaningful robust solution for individual parameters, convenient for interpretation of the results, and good for prediction. A tool from the cooperative game theory, the Shapley Value analysis, have been tried for estimation of regression coefficients and relative usefulness of the predictors in a model. This approach has been checked and successfully applied in various real-life projects in data analysts for commercial companies. It is useful for decision makers in economics, management, marketing research, and any other practical fields.

Keywords: Regression modeling, resistance to multicollinearity, Shapley Value regression

DOI: 10.3233/MAS-210529

Citation: Model Assisted Statistics and Applications, vol. 16, no. 2, pp. 165-168, 2021