Pub Date : 2022-04-01DOI: 10.1080/23737484.2021.2017807
Manabu Asai, Chia‐Lin Chang, M. McAleer, Laurent L. Pauwels
Abstract The article examines exchange-traded funds (ETFs) for green and sustainable energy regarding causality in their asset returns and volatilities. The structural vector autoregressive (VAR) model is one of the popular methodologies for the empirical analysis of macroeconomics and finance. However, the analysis is limited to the conditional mean, and excludes the structural analysis of conditional covariance models which measure the volatility and co-volatility of the financial asset returns. In order to accommodate this limitation, we develop a new structural multivariate GARCH-BEKK model that accommodates a dimension reduction for a BEKK-type parameterization of the time-varying covariance structure. We use a quasi-maximum likelihood estimator, which is shown to have consistency and asymptotic normality. For energy ETF returns, we construct the structural GARCH-BEKK model in order to investigate the causality in returns and volatility via statistical tests and impulse response functions, especially for two events, namely a drop in crude oil prices on May 5, 2011, and the Fukushima nuclear disaster on March 11, 2011. Our empirical results have found that for the portfolio renewable energy ETFs, Solar, Wind, and Water seem to exhibit indirect mutual causality effects in mean, and direct mutual causality effects in the second moment. When we incorporate the oil market into the renewable energy market, Oil seems to dominate the causality effects, so indirect uni- causality effects of the mean from the Oil to the Solar ETF, or Oil to the Water ETF, are found. However, there are no uni-causality or mutual causality effects in the second moment.
{"title":"A new structural multivariate GARCH-BEKK Model: Causality of green, sustainable and fossil energy ETFs","authors":"Manabu Asai, Chia‐Lin Chang, M. McAleer, Laurent L. Pauwels","doi":"10.1080/23737484.2021.2017807","DOIUrl":"https://doi.org/10.1080/23737484.2021.2017807","url":null,"abstract":"Abstract The article examines exchange-traded funds (ETFs) for green and sustainable energy regarding causality in their asset returns and volatilities. The structural vector autoregressive (VAR) model is one of the popular methodologies for the empirical analysis of macroeconomics and finance. However, the analysis is limited to the conditional mean, and excludes the structural analysis of conditional covariance models which measure the volatility and co-volatility of the financial asset returns. In order to accommodate this limitation, we develop a new structural multivariate GARCH-BEKK model that accommodates a dimension reduction for a BEKK-type parameterization of the time-varying covariance structure. We use a quasi-maximum likelihood estimator, which is shown to have consistency and asymptotic normality. For energy ETF returns, we construct the structural GARCH-BEKK model in order to investigate the causality in returns and volatility via statistical tests and impulse response functions, especially for two events, namely a drop in crude oil prices on May 5, 2011, and the Fukushima nuclear disaster on March 11, 2011. Our empirical results have found that for the portfolio renewable energy ETFs, Solar, Wind, and Water seem to exhibit indirect mutual causality effects in mean, and direct mutual causality effects in the second moment. When we incorporate the oil market into the renewable energy market, Oil seems to dominate the causality effects, so indirect uni- causality effects of the mean from the Oil to the Solar ETF, or Oil to the Water ETF, are found. However, there are no uni-causality or mutual causality effects in the second moment.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"219 1","pages":"215 - 233"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89373986","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}
Pub Date : 2022-03-28DOI: 10.1080/23737484.2022.2056546
R. P. Oliveira, J. Achcar, Charles Chen, Eliane R. Rodrigues
Abstract In this study we consider some stochastic models and a Bayesian approach to analyze count time series data in the presence of one or more change-points. When the observed count data are all different of zero, it is possible to perform an analysis using linear regression models with normal distribution errors for the log-transformed data. When we have the presence of zero counts at different times, the statistical model based on the log-transformation is not suitable. Hence, in this case, it is possible to consider non-homogeneous Poisson processes (NHPP) models with a suitable rate function. In the present work we consider both models (linear regression and Poisson) to analyze three data sets. These sets are data recording the monthly visitors to New Zealand with the purpose of education, yearly tuberculosis incidence data from New York City, and monthly measles incidence data from Brazil. When the NHPP model is used a PLP (power law process) model is assumed for the intensity function. Additionally, in both models, the presence of change-points will be allowed.
{"title":"Non-homogeneous Poisson and linear regression models as approaches to study time series with change-points","authors":"R. P. Oliveira, J. Achcar, Charles Chen, Eliane R. Rodrigues","doi":"10.1080/23737484.2022.2056546","DOIUrl":"https://doi.org/10.1080/23737484.2022.2056546","url":null,"abstract":"Abstract In this study we consider some stochastic models and a Bayesian approach to analyze count time series data in the presence of one or more change-points. When the observed count data are all different of zero, it is possible to perform an analysis using linear regression models with normal distribution errors for the log-transformed data. When we have the presence of zero counts at different times, the statistical model based on the log-transformation is not suitable. Hence, in this case, it is possible to consider non-homogeneous Poisson processes (NHPP) models with a suitable rate function. In the present work we consider both models (linear regression and Poisson) to analyze three data sets. These sets are data recording the monthly visitors to New Zealand with the purpose of education, yearly tuberculosis incidence data from New York City, and monthly measles incidence data from Brazil. When the NHPP model is used a PLP (power law process) model is assumed for the intensity function. Additionally, in both models, the presence of change-points will be allowed.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"72 1","pages":"331 - 353"},"PeriodicalIF":0.0,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84774952","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}
Pub Date : 2022-03-03DOI: 10.1080/23737484.2022.2043201
D. Kabata, A. Shintani
Abstract The different propensity score estimators reflect the average effect on the different populations. Particularly, it is pointed out that different causal inference methods based on propensity scores lead to entirely different conclusions when the treatment effect is not uniform across the study population. However, many clinical studies did not care about the difference in the estimands. To illustrate the difference in the estimated values depending on the propensity score methods in practice, were-analyzed a case study assessing the effects of surgical treatment among tongue cancer patients, which the treatment effect varied depending on the patients’ characteristics. Then we conducted a computer simulation to verify the results of the case study.
{"title":"Estimating the treatment effect with propensity score when the effect varies by patient characteristics: A case study and simulation","authors":"D. Kabata, A. Shintani","doi":"10.1080/23737484.2022.2043201","DOIUrl":"https://doi.org/10.1080/23737484.2022.2043201","url":null,"abstract":"Abstract The different propensity score estimators reflect the average effect on the different populations. Particularly, it is pointed out that different causal inference methods based on propensity scores lead to entirely different conclusions when the treatment effect is not uniform across the study population. However, many clinical studies did not care about the difference in the estimands. To illustrate the difference in the estimated values depending on the propensity score methods in practice, were-analyzed a case study assessing the effects of surgical treatment among tongue cancer patients, which the treatment effect varied depending on the patients’ characteristics. Then we conducted a computer simulation to verify the results of the case study.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"1 1","pages":"368 - 380"},"PeriodicalIF":0.0,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91334130","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}
Pub Date : 2022-03-02DOI: 10.1080/23737484.2022.2031346
Mohamed Saidane
Abstract In this paper, a computationally efficient Monte Carlo-based latent factor modeling approach for portfolio Value-at-Risk (VaR) estimation is introduced. We examine whether the inclusion of conditional heteroskedasticity in financial returns, and taking into account for possible hidden (Markovian) “regime changes” in the latent correlation structure of the portfolio can enhance the accuracy of VaR forecasts. Practical details of training such models with the expectation-maximization algorithm are also discussed. In conjunction with an approximated version of the Kalman filter, we show how to calculate maximum likelihood estimates of the model parameters, and to yield inferences about the unobservable path of the common factors, their volatilities and the hidden state sequence of the Markov process. The methodology is illustrated by an example using data from the Tunisian foreign exchange market, over the period of the Tunisian revolution from January 02, 2010 to December 30, 2012. We found that this new specification exhibits a good fit to the data, improves the accuracy of VaR predictions of the Tunisian foreign public debt portfolio and reduces the number and average size of back-testing breaches when a financial crisis occurs.
{"title":"Switching latent factor value-at-risk models for conditionally heteroskedastic portfolios: A comparative approach","authors":"Mohamed Saidane","doi":"10.1080/23737484.2022.2031346","DOIUrl":"https://doi.org/10.1080/23737484.2022.2031346","url":null,"abstract":"Abstract In this paper, a computationally efficient Monte Carlo-based latent factor modeling approach for portfolio Value-at-Risk (VaR) estimation is introduced. We examine whether the inclusion of conditional heteroskedasticity in financial returns, and taking into account for possible hidden (Markovian) “regime changes” in the latent correlation structure of the portfolio can enhance the accuracy of VaR forecasts. Practical details of training such models with the expectation-maximization algorithm are also discussed. In conjunction with an approximated version of the Kalman filter, we show how to calculate maximum likelihood estimates of the model parameters, and to yield inferences about the unobservable path of the common factors, their volatilities and the hidden state sequence of the Markov process. The methodology is illustrated by an example using data from the Tunisian foreign exchange market, over the period of the Tunisian revolution from January 02, 2010 to December 30, 2012. We found that this new specification exhibits a good fit to the data, improves the accuracy of VaR predictions of the Tunisian foreign public debt portfolio and reduces the number and average size of back-testing breaches when a financial crisis occurs.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"32 1","pages":"282 - 307"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78085949","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}
Pub Date : 2022-02-21DOI: 10.1080/23737484.2021.2019143
Ferebee Tunno, Latia Carraway
Abstract This article presents a new way to measure the volatility of financial time series, which is shown to be on a par with arc length for such endeavors. An application involving the clustering of 30 prominent stocks is presented as well.
{"title":"Bounded area as a measure of volatility for financial time series","authors":"Ferebee Tunno, Latia Carraway","doi":"10.1080/23737484.2021.2019143","DOIUrl":"https://doi.org/10.1080/23737484.2021.2019143","url":null,"abstract":"Abstract This article presents a new way to measure the volatility of financial time series, which is shown to be on a par with arc length for such endeavors. An application involving the clustering of 30 prominent stocks is presented as well.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"101 1","pages":"251 - 263"},"PeriodicalIF":0.0,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73419798","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}
Pub Date : 2022-02-07DOI: 10.1080/23737484.2022.2031345
E. Gayawan, O. Egbon, S. Adebayo
ABSTRACT Malaria infection, caused by plasmodium parasites, is a serious health challenge for children in the tropical regions. It becomes a serious life-threatening issue when the victim also suffers from anaemia because malaria parasite feeds on the iron particles present in the red blood cells. We consider a latent Gaussian model to jointly estimate the spatial patterns of co-morbidity from malaria and the different levels of anaemia among children under five years of age in Nigeria. The approach allows for response variables of different family of distribution to be jointly considered while accounting for metrical covariates as possible nonlinear effects and categorical variables as linear effects. Parameter estimation was through the integrated nested Laplace approximation. Our findings show similar spatial patterns of co-morbidity between malaria and severe anaemia and malaria and moderate anaemia but in the case of age of the child, the likelihoods of co-morbidity are similar for malaria and severe anaemia and malaria and mild anaemia. Urban residency, mother’s education, and household wealth index are consistently significant to the different forms of co-morbidity. Findings from the spatial effects avail decision-makers with location-specific evidence to prioritize and roll out interventions in a more judicious manner.
{"title":"Spatial modelling of the joint burden of malaria and anaemia co-morbidity in children: A Bayesian geoadditive perspective","authors":"E. Gayawan, O. Egbon, S. Adebayo","doi":"10.1080/23737484.2022.2031345","DOIUrl":"https://doi.org/10.1080/23737484.2022.2031345","url":null,"abstract":"ABSTRACT Malaria infection, caused by plasmodium parasites, is a serious health challenge for children in the tropical regions. It becomes a serious life-threatening issue when the victim also suffers from anaemia because malaria parasite feeds on the iron particles present in the red blood cells. We consider a latent Gaussian model to jointly estimate the spatial patterns of co-morbidity from malaria and the different levels of anaemia among children under five years of age in Nigeria. The approach allows for response variables of different family of distribution to be jointly considered while accounting for metrical covariates as possible nonlinear effects and categorical variables as linear effects. Parameter estimation was through the integrated nested Laplace approximation. Our findings show similar spatial patterns of co-morbidity between malaria and severe anaemia and malaria and moderate anaemia but in the case of age of the child, the likelihoods of co-morbidity are similar for malaria and severe anaemia and malaria and mild anaemia. Urban residency, mother’s education, and household wealth index are consistently significant to the different forms of co-morbidity. Findings from the spatial effects avail decision-makers with location-specific evidence to prioritize and roll out interventions in a more judicious manner.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"11 1","pages":"264 - 281"},"PeriodicalIF":0.0,"publicationDate":"2022-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81764489","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}
Pub Date : 2022-01-02DOI: 10.1080/23737484.2021.2010621
M. Hudnall, X. Yang, Yana Melnykov, Xuwen Zhu, Dwight Lewis, J. Parton
Abstract One key challenge of evaluating the effectiveness of opioid-related policies is to determine whether policy changes are associated with opioid prescription and usage. We explored this issue by employing a finite mixture of change point processes applied to US state-level opioid prescription data from 2006 to 2014. We identified clusters of states based on patterns of opioid prescription dosage per capita. The produced partitionings demonstrate some degree of geographic proximity when examined on the US map. Among the four drugs examined - methadone, buprenorphine, oxycodone, and hydrocodone – change points are detected for all drug classes except hydrocodone.
{"title":"Finite mixture modeling of change point processes to discover opioid prescribing patterns: A case study of automated reports and consolidated ordering system data","authors":"M. Hudnall, X. Yang, Yana Melnykov, Xuwen Zhu, Dwight Lewis, J. Parton","doi":"10.1080/23737484.2021.2010621","DOIUrl":"https://doi.org/10.1080/23737484.2021.2010621","url":null,"abstract":"Abstract One key challenge of evaluating the effectiveness of opioid-related policies is to determine whether policy changes are associated with opioid prescription and usage. We explored this issue by employing a finite mixture of change point processes applied to US state-level opioid prescription data from 2006 to 2014. We identified clusters of states based on patterns of opioid prescription dosage per capita. The produced partitionings demonstrate some degree of geographic proximity when examined on the US map. Among the four drugs examined - methadone, buprenorphine, oxycodone, and hydrocodone – change points are detected for all drug classes except hydrocodone.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"131 1","pages":"199 - 212"},"PeriodicalIF":0.0,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73175031","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}
Pub Date : 2022-01-01Epub Date: 2022-09-01DOI: 10.1080/23737484.2022.2115430
Panteha Hayati Rezvan, W Scott Comulada, M Isabel Fernández, Thomas R Belin
Health-science researchers often measure psychological constructs using multi-item scales and encounter missing items on some participants. Multiple imputation (MI) has emerged as an alternative to ad-hoc methods (e.g., mean substitution) for handling incomplete data on multi-item scales, appealingly reflecting available information while accounting for uncertainty due to missing values in a unified inferential framework. However, MI can be implemented in a variety of ways. When the number of variables to impute gets large, some strategies yield unstable estimates of quantities of interest while others are not technically feasible to implement. These considerations raise pragmatic questions about the extent to which ad-hoc procedures would yield statistical properties that are competitive with theoretically motivated methods. Drawing on an HIV study where depression and anxiety symptoms are measured with multi-item scales, this empirical investigation contrasts ad-hoc methods for handling missing items with various MI implementations that differ as to whether imputation is at the item-level or scale-level and how auxiliary variables are incorporated. While the findings are consistent with previous reports favoring item-level imputation when feasible to implement, we found only subtle differences in statistical properties across procedures, suggesting that weaknesses of ad-hoc procedures may be muted when missing data percentages are modest.
{"title":"Assessing Alternative Imputation Strategies for Infrequently Missing Items on Multi-item Scales.","authors":"Panteha Hayati Rezvan, W Scott Comulada, M Isabel Fernández, Thomas R Belin","doi":"10.1080/23737484.2022.2115430","DOIUrl":"10.1080/23737484.2022.2115430","url":null,"abstract":"<p><p>Health-science researchers often measure psychological constructs using multi-item scales and encounter missing items on some participants. Multiple imputation (MI) has emerged as an alternative to <i>ad-hoc</i> methods (e.g., mean substitution) for handling incomplete data on multi-item scales, appealingly reflecting available information while accounting for uncertainty due to missing values in a unified inferential framework. However, MI can be implemented in a variety of ways. When the number of variables to impute gets large, some strategies yield unstable estimates of quantities of interest while others are not technically feasible to implement. These considerations raise pragmatic questions about the extent to which <i>ad-hoc</i> procedures would yield statistical properties that are competitive with theoretically motivated methods. Drawing on an HIV study where depression and anxiety symptoms are measured with multi-item scales, this empirical investigation contrasts <i>ad-hoc</i> methods for handling missing items with various MI implementations that differ as to whether imputation is at the item-level or scale-level and how auxiliary variables are incorporated. While the findings are consistent with previous reports favoring item-level imputation when feasible to implement, we found only subtle differences in statistical properties across procedures, suggesting that weaknesses of <i>ad-hoc</i> procedures may be muted when missing data percentages are modest.</p>","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"8 4","pages":"682-713"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718541/pdf/nihms-1835512.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10190017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01Epub Date: 2022-09-22DOI: 10.1080/23737484.2022.2126414
Jiabu Ye, Dejian Lai, Lemuel A Moye, Barry R Davis
CCTRN is a Cardiovascular Cell Therapy Research Network. There were three randomized double blinded controlled stem cell clinical trials conducted in its first phase. The main results of these three clinical trials were published with conventional parametric models such as T test and nonparametric test such as Wilcoxon rank sum test without adjusting covariates. In this article, we conducted further analysis of the primary outcomes of these studies using a class of covariate adjusted nonparametric methods.
{"title":"Applications of Covariate Adjusted Nonparametric Methods to CCTRN Clinical Trials.","authors":"Jiabu Ye, Dejian Lai, Lemuel A Moye, Barry R Davis","doi":"10.1080/23737484.2022.2126414","DOIUrl":"10.1080/23737484.2022.2126414","url":null,"abstract":"<p><p>CCTRN is a Cardiovascular Cell Therapy Research Network. There were three randomized double blinded controlled stem cell clinical trials conducted in its first phase. The main results of these three clinical trials were published with conventional parametric models such as T test and nonparametric test such as Wilcoxon rank sum test without adjusting covariates. In this article, we conducted further analysis of the primary outcomes of these studies using a class of covariate adjusted nonparametric methods.</p>","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"8 4","pages":"728-737"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181848/pdf/nihms-1847500.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9462453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-28DOI: 10.1080/23737484.2021.2017809
Dhruba Das, H. Saikia, Dibyojyoti Bhattacharjee, Bhaskar Kushvaha
ABSTRACT In cricket, the prime responsibility lies with the batsmen of a team to do the bulk of the scoring. Therefore, the strategy of playing shots is more specific to the batsmen and all-rounders of the team. Based on the match situation, a batsman must play either defensively to defend his wicket or bat aggressively to progress his team’s total score. Given the expertise of the batsman, the captain of the fielding team shall decide which bowler to bowl and place the fielders in such a way that a batsman find it difficult to score runs. However, the fielding arrangement depends on the type of bowler (i.e., either fast or spin). Therefore, this study tries to determine the probabilistic estimation of shot selection by a batsman against bowling type after dividing the entire cricket field into six different nonoverlapping areas. Initially, the probabilities of shots played by a batsman are estimated using multinomial distribution. Thereafter, transition probabilities of shots for a batsman along with mean recurrence time are estimated using Markov chain. This study will be helpful for the captain of the fielding team to arrange the fielder and choose his bowlers against a given batsman of the opponent team.
{"title":"On estimating shot selection by a batsman in Twenty20 cricket: A probabilistic approach","authors":"Dhruba Das, H. Saikia, Dibyojyoti Bhattacharjee, Bhaskar Kushvaha","doi":"10.1080/23737484.2021.2017809","DOIUrl":"https://doi.org/10.1080/23737484.2021.2017809","url":null,"abstract":"ABSTRACT In cricket, the prime responsibility lies with the batsmen of a team to do the bulk of the scoring. Therefore, the strategy of playing shots is more specific to the batsmen and all-rounders of the team. Based on the match situation, a batsman must play either defensively to defend his wicket or bat aggressively to progress his team’s total score. Given the expertise of the batsman, the captain of the fielding team shall decide which bowler to bowl and place the fielders in such a way that a batsman find it difficult to score runs. However, the fielding arrangement depends on the type of bowler (i.e., either fast or spin). Therefore, this study tries to determine the probabilistic estimation of shot selection by a batsman against bowling type after dividing the entire cricket field into six different nonoverlapping areas. Initially, the probabilities of shots played by a batsman are estimated using multinomial distribution. Thereafter, transition probabilities of shots for a batsman along with mean recurrence time are estimated using Markov chain. This study will be helpful for the captain of the fielding team to arrange the fielder and choose his bowlers against a given batsman of the opponent team.","PeriodicalId":36561,"journal":{"name":"Communications in Statistics Case Studies Data Analysis and Applications","volume":"23 1","pages":"354 - 367"},"PeriodicalIF":0.0,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75530779","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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