Model Assisted Statistics and Applications - Volume 17, issue 2

Article Type: Other

DOI: 10.3233/MAS-220009

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 69-, 2022

Article Type: Review Article

DOI: 10.3233/MAS-220010

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 71-72, 2022

Authors: Chandra, Hukum | Verma, Bhanu

Article Type: Research Article

Abstract: The 2 nd Sustainable Development Goal (SDG) of the United Nations attempt to eliminate the potential hunger and food insecurity issues by 2030, but in the plight of COVID19 pandemic it has become far more critical and persistent issue globally as well as in India. The nation-wide socio-economic surveys of National Sample Survey Office (NSSO) in India are designed to produce reliable and representative estimates of important food insecurity parameters at state and national level for both rural and urban sectors separately but these surveys cannot be used directly to generate reliable district level estimates. Whereas, …efficient and representative disaggregated level estimates for the extent (or incidence) of food insecurity prevalence has direct impact on strategizing effective policy plans and monitoring progress towards eliminating food insecurity. In this backdrop, the paper outlines small area estimation approach to estimate the incidence of food insecurity across the districts of rural Uttar Pradesh in India by linking data from the 2011–12 Household Consumer Expenditure Survey of NSSO, and the 2011 Indian Population Census. A spatial map has been generated showing spatial disparity for the incidence of food insecurity in Uttar Pradesh. These disaggregated level estimates are relevant and purposeful for SDG indicator 2.1.2 – severity of food insecurity. The estimates and map of food insecurity incidences are expected to deliver invaluable information to the policy-analysts and decision-makers. Show more

Keywords: Food insecurity, sustainable development goal, small area estimation, precise, representative, rural districts

DOI: 10.3233/MAS-220011

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 73-85, 2022

Authors: Kaur, Manpreet | Grewal, Inderjit Singh | Sidhu, Sukhjinder Singh

Article Type: Research Article

Abstract: Getting correct answers to sensitive questions from the respondents and estimating the population parameters on variables that are sensitive in nature is prevailing problem in survey sampling. In the present research paper, the problem of estimation of the population proportion of sensitive characteristics has been studied. For this, an improved randomized response device has been developed by taking the two cases of the unrelated question, case-I: ‘when the proportion of unrelated characteristic is known’ and other case-II: ‘when the proportion of unrelated characteristic is not known’. Two estimators of the population proportion of a sensitive characteristic have been proposed, one …for a known value of unrelated characteristic π y and the other for an unknown value, which were found to be unbiased. The expression for variances and unbiased estimates for the variances of the proposed estimators have been obtained. The optimum value of sample sizes has been worked out for which the minimum variance for the proposed estimators has also been obtained. An empirical study has been conducted and concluded graphically that proposed estimators are better than the estimators of Mangat (1992) and Tiwari and Mehta (2016). Show more

Keywords: Randomized response technique, unbiased estimator, variance, relative efficiency

DOI: 10.3233/MAS-220012

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 87-97, 2022

Authors: Chebout, Mohamed Sedik | Kabour, Oussama

Article Type: Research Article

Abstract: Currently, the Algerian health system is facing the fourth wave of COVID-19 in which the number of recovered cases grows exponentially each day due to the COVID-19 Omicron variant. According to the Algerian National Institute of Public Health (ANIPH), it was reported 168 668 confirmed cases and 4 189 deaths till 29 July, 2021. In this work, we aim to utilize supervised Machine Learning (ML) based models in an attempt to forecast the future trend of the disease in Algeria. To that end, we use three forecasting models: Facebook Prophet, LSTM and ARIMA. Forecasting results of the 90 future days are provided. …The used dataset contains the confirmed and death cases collected from the daily Epidemiological Situation (ES), published by ANIPH, from 19 April 2020 to 29 July 2021. The forecasting accuracy of the models are assessed and compared using several statistical assessment criteria. The results show that ARIMA outperforms Facebook Prophet and LSTM in the case of confirmed cases. However, LSTM shows best performance in the case of death cases. This study shows clearly that the pandemic spread is still in progress and protection measures like contact restriction and lockdown should be strictly applied especially with the appearance of the COVID-19 Delta and Omicron variants. Show more

Keywords: COVID-19, Delta variant, Algeria, Machine Learning, Forecasting

DOI: 10.3233/MAS-220013

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 99-108, 2022

Authors: Kumari, Ritu | Arora, Sangeeta | Mahajan, Kalpana K.

Article Type: Research Article

Abstract: In this paper, classical as well as Bayesian estimation of stress strength reliability ( η ) of Dagum distribution under progressive type-II censored sample is done. Maximum likelihood estimators (MLEs) of η are also obtained along with asymptotic, bootstrap-p (boot-p) and bootstrap-t (boot-t) confidence intervals. Bayes estimators of η along with highest posterior density (HPD) credible intervals based on informative and non-informative priors are also obtained. Symmetric as well as asymmetric loss functions are considered for the Bayesian estimation. Monte Carlo simulation study is carried out to check the performance …of estimators. Real life data sets are considered for illustration purpose. Show more

Keywords: Dagum distribution, stress-strength reliability, Bayes estimators, maximum likelihood estimators

DOI: 10.3233/MAS-220014

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 109-122, 2022

Authors: Aguilar, Guilherme Aparecido Santos | Moala, Fernando A. | de Oliveira, Ricardo Puziol

Article Type: Research Article

Abstract: Different methods for obtaining new probability distributions have been introduced in the literature in recent years, for example, (Gupta et al., 1998) proposed an interesting uni-parametric lifetime distribution, Exponentiated Gamma (EG), which hazard function has increasing and bathtub shapes. In this paper, we build a new two-parameters distribution, the Marshall Olkin Extended Exponentiated Gamma (MOEEG) distribution, which is derived from the Marshall-Olkin method and the EG distribution. The hazard function of this new distribution can accommodate monotonic, non-monotonic and unimodal shapes, allowing a better fit to greater data variability. In addition to the great flexibility of fitting the data, it …contains only two parameters providing a simple parameter estimation procedure, unlike other distributions proposed in the literature that have three or more parameters. Some properties of the new distribution considered in this paper are presented such as n -th time, r -th moment of residual life, r -thmoment of residual life inverted, stochastic ordering, entropy, mean deviation, Bonferroni and Lorenz curve, skewness, kurtosis, order statistics, and stress-strength parameter. We also apply two different estimation methods, maximum likelihood and Bayesian approach. Real data applications are presented to illustrate the usefulness of this new distribution. Show more

Keywords: Marshall-Olkin Extended Exponentiated Gamma, Marshall Olkin, maximum likelihood, Bayesian estimators, failure rate function

DOI: 10.3233/MAS-220015

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 123-141, 2022

Article Type: Other

DOI: 10.3233/MAS-220016

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 143-, 2022

Authors: Lipovetsky, Stan

Article Type: Research Article

Abstract: The work considers various multivariate statistical techniques in their modifications and applications to management, information systems, economics, decision making, and marketing research problems. The methods include eigenvectors for many-way matrices, dual partial lest squares, modified factor and cluster analyses, and enhanced canonical correlation analysis. These approaches have been applied in numerous real projects and proved to be useful for data analysts, managers, and decision makers in solving practical problems.

Keywords: Multidimensional matrices, three-way SVD and PCA, Dual PLS, factor and cluster analyses, robust and orthonormal canonical correlations

DOI: 10.3233/MAS-220017

Citation: Model Assisted Statistics and Applications, vol. 17, no. 2, pp. 145-147, 2022