Statistical and decision-making techniques for solving prioritization problems are described. These approaches include the analytic hierarchy process (AHP) of the multi-attribute decision-making and its extension to the statistical modeling and testing, scaling techniques of priority estimation, maximum difference models, identification of key drivers in regression, and other methods. The described techniques have been widely applied and proved to be helpful for identification and ordering the most important items in solving various marketing research and decision-making problems.
{"title":"Prioritization and decision-making: A brief review of methods","authors":"S. Lipovetsky","doi":"10.3233/mas-230951","DOIUrl":"https://doi.org/10.3233/mas-230951","url":null,"abstract":"Statistical and decision-making techniques for solving prioritization problems are described. These approaches include the analytic hierarchy process (AHP) of the multi-attribute decision-making and its extension to the statistical modeling and testing, scaling techniques of priority estimation, maximum difference models, identification of key drivers in regression, and other methods. The described techniques have been widely applied and proved to be helpful for identification and ordering the most important items in solving various marketing research and decision-making problems.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47901808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modeling DNA sequences with stochastic models and developing statistical methods to analyze the multiple projects of DNA sequencing are challenging questions for statisticians and biologists. Some of the most manifestations are the study of long-range dependence in DNA sequences that transform the DNA sequence into a numerical time series to study the long-range dependence in a DNA sequence. It is still discussed in the works if the type of transformation can alter the conclusion of long-range dependence on the DNA sequence. Here we model the DNA sequence considering the Fractional Poisson Process, propose a method based on moments for estimating the parameters of the Fractional Poisson Process in the DNA sequence, and analyze the long-range dependence in various DNA sequences by the detrended fluctuation analysis method.
{"title":"Fractional poisson process: Long-range dependence in DNA sequences","authors":"R. Linhares","doi":"10.3233/mas-210375","DOIUrl":"https://doi.org/10.3233/mas-210375","url":null,"abstract":"Modeling DNA sequences with stochastic models and developing statistical methods to analyze the multiple projects of DNA sequencing are challenging questions for statisticians and biologists. Some of the most manifestations are the study of long-range dependence in DNA sequences that transform the DNA sequence into a numerical time series to study the long-range dependence in a DNA sequence. It is still discussed in the works if the type of transformation can alter the conclusion of long-range dependence on the DNA sequence. Here we model the DNA sequence considering the Fractional Poisson Process, propose a method based on moments for estimating the parameters of the Fractional Poisson Process in the DNA sequence, and analyze the long-range dependence in various DNA sequences by the detrended fluctuation analysis method.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44048776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sampling frames are mostly incomplete in large scale surveys. This paper suggests the use of probability proportional to size with replacement (PPSWR) sampling scheme for estimation of population mean with an incomplete frame. The variance of the estimators has been obtained and its efficiency has been compared with Agarwal and Gupta (2008) estimator when the frame is not complete. The results obtained have been illustrated with the help of hypothetical data. The problem of determining optimum sample size and retainment factor has also been discussed using a suitable linear cost function.
{"title":"Estimation with incomplete frames using varying probability sampling with replacement","authors":"Jyoti, Sarla Pareek, P. C. Gupta","doi":"10.3233/mas-221379","DOIUrl":"https://doi.org/10.3233/mas-221379","url":null,"abstract":"Sampling frames are mostly incomplete in large scale surveys. This paper suggests the use of probability proportional to size with replacement (PPSWR) sampling scheme for estimation of population mean with an incomplete frame. The variance of the estimators has been obtained and its efficiency has been compared with Agarwal and Gupta (2008) estimator when the frame is not complete. The results obtained have been illustrated with the help of hypothetical data. The problem of determining optimum sample size and retainment factor has also been discussed using a suitable linear cost function.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44195646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 compared. An empirical study, based on both vegetable crop data and simulated data, has been performed to find out the best estimator. It has been seen that out of the two proposed estimators, the ratio cum dual to ratio type estimator performed better than dual to ratio estimator.
{"title":"Two new estimators of finite population variance under random non-response: An application","authors":"Alisha Mittal, M. Kumar","doi":"10.3233/mas-221361","DOIUrl":"https://doi.org/10.3233/mas-221361","url":null,"abstract":"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 compared. An empirical study, based on both vegetable crop data and simulated data, has been performed to find out the best estimator. It has been seen that out of the two proposed estimators, the ratio cum dual to ratio type estimator performed better than dual to ratio estimator.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48355040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. P. de Oliveira, Marcos Vinicius de Oliveira Peres, Wesley Bertoli, J. Achcar
The present study considers non-mixture models based on the discrete Burr XIII distribution to model recurrent event data in the presence of a cure fraction. In this context, we provide an alternative to the standard Cox proportional hazards model using a discretized distribution to analyze lifetime data assuming a non-mixture structure for cure rates. In a Bayesian setting, the proposed methodology was considered for analyzing a real dataset from a retrospective cohort study that aimed to evaluate specific clinical conditions that affect the lifetimes of 299 heart failure patients admitted to the Institute of Cardiology and Allied Hospital – Faisalabad, Pakistan (April-December, 2015). The model validation process was addressed using the Cox-Snell residuals, which allowed us to identify the suitability of the proposed non-mixture cure rate model.
{"title":"A non-mixture cure rate model for analyzing the survival lifetimes of cardiovascular heart failure patients","authors":"R. P. de Oliveira, Marcos Vinicius de Oliveira Peres, Wesley Bertoli, J. Achcar","doi":"10.3233/mas-221341","DOIUrl":"https://doi.org/10.3233/mas-221341","url":null,"abstract":"The present study considers non-mixture models based on the discrete Burr XIII distribution to model recurrent event data in the presence of a cure fraction. In this context, we provide an alternative to the standard Cox proportional hazards model using a discretized distribution to analyze lifetime data assuming a non-mixture structure for cure rates. In a Bayesian setting, the proposed methodology was considered for analyzing a real dataset from a retrospective cohort study that aimed to evaluate specific clinical conditions that affect the lifetimes of 299 heart failure patients admitted to the Institute of Cardiology and Allied Hospital – Faisalabad, Pakistan (April-December, 2015). The model validation process was addressed using the Cox-Snell residuals, which allowed us to identify the suitability of the proposed non-mixture cure rate model.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47480962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Cordeiro, F. Prataviera, E. Ortega, R. Vila, Erica V. Nogueira
We define the odd extended log-logistic-G family, and obtain some of its statistical properties. We construct a new extended regression based on the logarithm of the proposed distribution, which can be better than other known regressions to fit real data.
{"title":"The odd extended log-logistic family: Properties, regression, simulations and applications","authors":"G. Cordeiro, F. Prataviera, E. Ortega, R. Vila, Erica V. Nogueira","doi":"10.3233/mas-221364","DOIUrl":"https://doi.org/10.3233/mas-221364","url":null,"abstract":"We define the odd extended log-logistic-G family, and obtain some of its statistical properties. We construct a new extended regression based on the logarithm of the proposed distribution, which can be better than other known regressions to fit real data.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47333055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A New Section in MASA: Guide Handbook of Statistical Techniques (GHOST)","authors":"","doi":"10.3233/mas-230950","DOIUrl":"https://doi.org/10.3233/mas-230950","url":null,"abstract":"","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136126800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kumar Abhinandan Sood, Aditi K. Darekar, Prabhat Mishra, Barsharani Maharana, S. Kumar
Conjoint Analysis is an analytical technique used in market research to quantify consumer preferences for a product or service. The result of the technique provides us with different combinations of attributes that consumers value the most. The technique uses different features of a product or service and their corresponding levels to model and quantifies the customers’ buying decision process. Using Conjoint Analysis, one can study the trade-offs undertaken by the consumer and use the derived insights for design implementation. The sale of Bluetooth Earphones in India witnessed a sudden spike during the COVID 19 pandemic. The consequential market, thriving with competition, saw market leaders attempt to strengthen their positions further and new players try to enter the market. The paper seeks to understand the existing consumer preferences for different features of Bluetooth Earphones using Conjoint Analysis. The outcome of the analysis provides market stakeholders with a yardstick to guide their design decisions and formulate sustainable long-term business strategies.
{"title":"“Feel the decibels closely”: Earphones preference study using conjoint analysis","authors":"Kumar Abhinandan Sood, Aditi K. Darekar, Prabhat Mishra, Barsharani Maharana, S. Kumar","doi":"10.3233/mas-220409","DOIUrl":"https://doi.org/10.3233/mas-220409","url":null,"abstract":"Conjoint Analysis is an analytical technique used in market research to quantify consumer preferences for a product or service. The result of the technique provides us with different combinations of attributes that consumers value the most. The technique uses different features of a product or service and their corresponding levels to model and quantifies the customers’ buying decision process. Using Conjoint Analysis, one can study the trade-offs undertaken by the consumer and use the derived insights for design implementation. The sale of Bluetooth Earphones in India witnessed a sudden spike during the COVID 19 pandemic. The consequential market, thriving with competition, saw market leaders attempt to strengthen their positions further and new players try to enter the market. The paper seeks to understand the existing consumer preferences for different features of Bluetooth Earphones using Conjoint Analysis. The outcome of the analysis provides market stakeholders with a yardstick to guide their design decisions and formulate sustainable long-term business strategies.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46940433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A global revolution is called upon to transition into renewable sources of energy from fossil fuels in an accelerated manner by various countries to become net zero carbon emitter with self-committed timelines. This study identified carbon dioxide emissions and participation of renewable energy in total energy supply as two major dimensions and discusses the impact of various independent variables quantitively by multipanel regression in timeseries and countries for comparative correlation analysis. Theme based industry expert interviews adds qualitative dimension to the study. The results suggest that country’s energy need and availability of fossil fuels within, determines the RE adoption rate, while countries with high reliance on coal and crude are shifting towards RE sources. Investments in research and development in hydrogen, fuel cells and storage are yet to make an impact in this direction since they are recent in this long game of energy transition.
{"title":"Industrial adoption and transition towards sustainable renewable energy","authors":"Nishesh Garg, N. Gupta","doi":"10.3233/mas-220406","DOIUrl":"https://doi.org/10.3233/mas-220406","url":null,"abstract":"A global revolution is called upon to transition into renewable sources of energy from fossil fuels in an accelerated manner by various countries to become net zero carbon emitter with self-committed timelines. This study identified carbon dioxide emissions and participation of renewable energy in total energy supply as two major dimensions and discusses the impact of various independent variables quantitively by multipanel regression in timeseries and countries for comparative correlation analysis. Theme based industry expert interviews adds qualitative dimension to the study. The results suggest that country’s energy need and availability of fossil fuels within, determines the RE adoption rate, while countries with high reliance on coal and crude are shifting towards RE sources. Investments in research and development in hydrogen, fuel cells and storage are yet to make an impact in this direction since they are recent in this long game of energy transition.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48829926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The current practice of option price forecast relies on the outputs of various option pricing models. The expected value of the current option price is widely regarded as the best forecast for the future price, assuming the option prices evolve with a Brownian motion. However, volatility clustering, transaction illiquidity, and demand-supply imbalance drive the future option prices off the modeled price targets. Therefore, we suggest using the spline method to forecast option prices directly. The focus is the accuracy of the forecasted asset price in the next period, rather than if the pricing models correctly produce the current price. We use fifteen years of daily SPY American option contract prices to examine the spline model forecast accuracy. Among the 476,882 forecasts produced, the mean forecasting error size is $3.66 × 10-3, with a standard deviation of 1.33 and a median error of $5.54 × 10-17. The forecast accuracy is stable across contracts with different terms and moneyness. The spline forecast model incorporates the illiquidity issue and avoids the vital pitfalls in the current leading option pricing techniques.
{"title":"Option price predictability, splines, and expanded rationality","authors":"Huijian Dong, Xiaomin Guo","doi":"10.3233/mas-220410","DOIUrl":"https://doi.org/10.3233/mas-220410","url":null,"abstract":"The current practice of option price forecast relies on the outputs of various option pricing models. The expected value of the current option price is widely regarded as the best forecast for the future price, assuming the option prices evolve with a Brownian motion. However, volatility clustering, transaction illiquidity, and demand-supply imbalance drive the future option prices off the modeled price targets. Therefore, we suggest using the spline method to forecast option prices directly. The focus is the accuracy of the forecasted asset price in the next period, rather than if the pricing models correctly produce the current price. We use fifteen years of daily SPY American option contract prices to examine the spline model forecast accuracy. Among the 476,882 forecasts produced, the mean forecasting error size is $3.66 × 10-3, with a standard deviation of 1.33 and a median error of $5.54 × 10-17. The forecast accuracy is stable across contracts with different terms and moneyness. The spline forecast model incorporates the illiquidity issue and avoids the vital pitfalls in the current leading option pricing techniques.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48253447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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