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Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra
| Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (318 pages) |
| Disciplina | 519.54 |
| Collana | Springer Proceedings in Mathematics and Statistics Ser. |
| Soggetto topico | Mathematical statistics |
| ISBN | 981-16-7932-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Obituary -- Contents -- Editors and Contributors -- Bayesian Order-Restricted Inference of Multinomial Counts from Small Areas -- 1 Introduction -- 2 Multinomial Dirichlet Models -- 2.1 Model Without Order Restriction (M1) -- 2.2 Model with Order Restrictions (M2) -- 3 Computations -- 3.1 Sampling θ in M2 -- 3.2 Gibbs Sampling for µ and τ -- 4 Application to BMI -- 4.1 Body Mass Index -- 4.2 MCMC Convergence -- 4.3 Model Comparison -- 5 Bayesian Diagnostics -- 6 Conclusion -- 7 Appendix -- 7.1 Details of Gibbs Sampling for µ and τ -- 7.2 Model Comparison -- References -- A Hierarchical Bayesian Beta-Binomial Model for Sub-areas -- 1 Introduction -- 2 Hierarchical Bayesian Small Area Models -- 2.1 A One-Fold Beta-Binomial Model -- 2.2 A Two-Fold Beta-Binomial Model -- 3 Computation -- 3.1 Approximation Method -- 3.2 Exact Method -- 4 Numerical Example -- 4.1 Nepal Living Standards Survey II -- 4.2 Numerical Comparison -- 5 Conclusion and Future Work -- Appendix A Some Details about Approximation of π(µi |τ) -- Appendix B Propriety of the One-Fold Model -- References -- Hierarchical Bayes Inference from Survey-Weighted Small Domain Proportions -- 1 Introduction -- 2 Hierarchical Bayesian Framework -- 3 Application -- 4 Concluding Remarks -- References -- Efficiency of Ranked Set Sampling Design in Goodness of Fit Tests for Cauchy Distribution -- 1 Introduction -- 2 Goodness of Fit Test for Cauchy Distribution -- 3 Power Comparison -- 4 Conclusion -- References -- Fuzzy Supply Chain Newsboy Problem Under Lognormal Distributed Demand for Bakery Products -- 1 Introduction -- 2 Preliminary Definitions and Mathematical Model -- 2.1 Notations and Assumptions -- 2.2 Mathematical Model -- 3 Numerical Case Study -- 4 Results and Discussion -- 5 Conclusions -- References.
Probabilistic Supply Chain Models with Partial Backlogging for Deteriorating Items -- 1 Introduction -- 2 Mathematical Model -- 2.1 Preliminaries -- 3 Genetic Algorithm -- 4 Numerical Example -- 5 Sensitivity Analysis -- 6 Managerial Implications -- 7 Conclusions -- References -- The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Prediction -- 1 Introduction -- 2 Evolution of Dynamic Gaussian Process Model -- 2.1 Basic Gaussian Process Model -- 2.2 Dynamic Gaussian Process Model -- 2.3 Generalizations for Big Data -- 3 Application: Malaria Vaccination Coverage -- 4 Concluding Remarks -- References -- Grey Relational Analysis for the Selection of Potential Isolates of Alternaria Alternata of Poplar -- 1 Introduction -- 2 Material and Methods -- 2.1 Survey and Collection of Alternaria Isolates -- 2.2 GRA for Selection of Potent Isolates -- 3 Results -- 3.1 Growth Attributes of A. Alternata -- 3.2 Grey Relational Generating, Coefficients and Grades -- 3.3 Performance Evaluation of Selected Isolates -- 4 Discussion and Conclusion -- References -- Decision Making for Multi-Items Inventory Models -- 1 Introduction -- 2 Notations and Assumptions -- 2.1 Assumptions -- 2.2 Notations -- 3 Mathematical Model -- 4 Numerical Example and Comparison Study -- 5 Conclusion -- References -- Modeling Australian Twin Data Using Generalized Lindley Shared Frailty Models -- 1 Introduction -- 2 Reversed Hazard Rate -- 3 General Shared Frailty Model -- 4 Generalized Lindley Frailty Model -- 5 Dependence Measure -- 6 Baseline Distributions -- 6.1 Modified Inverse Weibull Distribution -- 6.2 Generalized Rayleigh Distribution -- 7 Proposed Models -- 8 Statistical Properties -- 8.1 Bivariate Density Function -- 8.2 Bivariate Survival Function -- 8.3 Hazard Gradient Function -- 8.4 Conditional Probability Measure. 8.5 Cross-ratio Function -- 9 Likelihood Design and Bayesian Paradigm -- 10 Simulation Study -- 11 Analysis of Australian Twin Data -- 12 Conclusions -- References -- Ultimate Ruin Probability for Benktander Gibrat Risk Model -- 1 Introduction -- 2 Risk Model -- 3 Laplace Transformation -- 4 Ultimate Ruin Probability for BG Distribution -- 5 Calculation of Ultimate Ruin Probability -- 6 Conclusions -- References -- Test of Homogeneity of Scale Parameters Based on Function of Sample Quasi Ranges -- 1 Introduction -- 2 Proposed Test Procedure -- 3 Calculation of Critical Points for Some Specific Distributions: Simulation Method -- 3.1 Critical Points for Standard Exponential, Standard Logistic and Standard Uniform Distributions -- 4 Simultaneous One-Sided Confidence Intervals (SOCI's) of the Proposed Test -- 4.1 Simulated Example to Compute Test Statistic and SOCIs -- 5 Power of the Proposed Test -- 6 Conclusion -- References -- A Bayesian Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent Randomization Method for SMART Designs -- 1 Introduction -- 2 Methods -- 2.1 Overview of the SMART Design -- 2.2 Randomization Probability Using Q-Learning-Based Optimal Decisions -- 2.3 Covariate-Balanced Randomization Probability According to the Prognostic Score for SMART Designs -- 2.4 Response-Adaptive Randomization Probability Based on Outcomes of Previous Groups -- 2.5 Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent (RCQ) Randomization Method -- 3 Simulations Models and Assessment Measures -- 3.1 Simulation Models -- 3.2 Assessment Measures -- 3.3 Simulation Results -- 4 Discussion -- References -- An Introduction to Bayesian Inference for Finite Population Characteristics -- 1 Introduction -- 2 Normal Distribution -- 3 Regression -- 4 Dirichlet Process -- 5 Multiple Regression with Post-stratification. 6 Categorical Data -- 7 Summary and Discussion -- References -- Reliability Measures of Repairable Systems with Arrival Time of Server -- 1 Introduction -- 2 Literature Review -- 3 Some Fundamentals -- 3.1 Reliability -- 3.2 Mean Time to System Failure (MTSF) -- 3.3 Steady-State Availability -- 3.4 Redundancy -- 3.5 Semi-Markov Process -- 3.6 Regenerative Point Process -- 4 Common Notations -- 5 Reliability Measures of Repairable Systems -- 5.1 MTSF and Availability of a Single Unit System with Arrival Time of the Server -- 5.2 MTSF and Availability of a Two-Unit Cold Standby System with Arrival Time of the Server -- 5.3 MTSF and Availability of a Two-Unit Parallel System with Arrival Time of the Server -- 6 Discussion and Conclusion -- References -- Stress-strength Reliability Estimation for Multi-component System Based on Upper Record Values Under New Weibull-Pareto Distribution -- 1 Introduction -- 2 System Reliability -- 3 Maximum Likelihood Estimators (MLE) of Parameters -- 4 Likelihood Ratio (LR) Test for Equality of Scale Parameters -- 5 Estimation of Rs,k Using Maximum Likelihood and Bayesian Methods -- 6 Simulation Study -- 7 Real Data Analysis -- 8 Summary and Conclusions -- References -- Record Values and Associated Inference on Muth Distribution -- 1 Introduction -- 2 Survival Function, Joint and Conditional Densities, and Moments of Upper Records from Muth Distribution -- 3 Parameter Estimation Based on Upper Records Using Moment, Likelihood, and Bayesian Approaches -- 3.1 Moment Estimation of α -- 3.2 Maximum Likelihood Estimation -- 3.3 Bayesian Estimation -- 4 Numerical Illustration -- 5 Real-life Application -- 6 Prediction of Future Records -- 6.1 Frequentist Approach -- 6.2 Bayesian Approach -- 7 Concluding Remarks -- References -- Statistical Linear Calibration in Data with Measurement Errors -- 1 Introduction. 2 Development of Calibration Estimators -- 3 Performance Properties -- 3.1 Large Sample Asymptotic Bias (LSAB) -- 3.2 Large Sample Asymptotic Variance (LSAV) -- 4 An Example -- 5 Conclusions -- References. |
| Record Nr. | UNISA-996472038403316 |
| Gateway East, Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra
| Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (318 pages) |
| Disciplina | 519.54 |
| Collana | Springer Proceedings in Mathematics and Statistics |
| Soggetto topico |
Mathematical statistics
Estadística matemàtica |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
981-16-7931-2
981-16-7932-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Obituary -- Contents -- Editors and Contributors -- Bayesian Order-Restricted Inference of Multinomial Counts from Small Areas -- 1 Introduction -- 2 Multinomial Dirichlet Models -- 2.1 Model Without Order Restriction (M1) -- 2.2 Model with Order Restrictions (M2) -- 3 Computations -- 3.1 Sampling θ in M2 -- 3.2 Gibbs Sampling for µ and τ -- 4 Application to BMI -- 4.1 Body Mass Index -- 4.2 MCMC Convergence -- 4.3 Model Comparison -- 5 Bayesian Diagnostics -- 6 Conclusion -- 7 Appendix -- 7.1 Details of Gibbs Sampling for µ and τ -- 7.2 Model Comparison -- References -- A Hierarchical Bayesian Beta-Binomial Model for Sub-areas -- 1 Introduction -- 2 Hierarchical Bayesian Small Area Models -- 2.1 A One-Fold Beta-Binomial Model -- 2.2 A Two-Fold Beta-Binomial Model -- 3 Computation -- 3.1 Approximation Method -- 3.2 Exact Method -- 4 Numerical Example -- 4.1 Nepal Living Standards Survey II -- 4.2 Numerical Comparison -- 5 Conclusion and Future Work -- Appendix A Some Details about Approximation of π(µi |τ) -- Appendix B Propriety of the One-Fold Model -- References -- Hierarchical Bayes Inference from Survey-Weighted Small Domain Proportions -- 1 Introduction -- 2 Hierarchical Bayesian Framework -- 3 Application -- 4 Concluding Remarks -- References -- Efficiency of Ranked Set Sampling Design in Goodness of Fit Tests for Cauchy Distribution -- 1 Introduction -- 2 Goodness of Fit Test for Cauchy Distribution -- 3 Power Comparison -- 4 Conclusion -- References -- Fuzzy Supply Chain Newsboy Problem Under Lognormal Distributed Demand for Bakery Products -- 1 Introduction -- 2 Preliminary Definitions and Mathematical Model -- 2.1 Notations and Assumptions -- 2.2 Mathematical Model -- 3 Numerical Case Study -- 4 Results and Discussion -- 5 Conclusions -- References.
Probabilistic Supply Chain Models with Partial Backlogging for Deteriorating Items -- 1 Introduction -- 2 Mathematical Model -- 2.1 Preliminaries -- 3 Genetic Algorithm -- 4 Numerical Example -- 5 Sensitivity Analysis -- 6 Managerial Implications -- 7 Conclusions -- References -- The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Prediction -- 1 Introduction -- 2 Evolution of Dynamic Gaussian Process Model -- 2.1 Basic Gaussian Process Model -- 2.2 Dynamic Gaussian Process Model -- 2.3 Generalizations for Big Data -- 3 Application: Malaria Vaccination Coverage -- 4 Concluding Remarks -- References -- Grey Relational Analysis for the Selection of Potential Isolates of Alternaria Alternata of Poplar -- 1 Introduction -- 2 Material and Methods -- 2.1 Survey and Collection of Alternaria Isolates -- 2.2 GRA for Selection of Potent Isolates -- 3 Results -- 3.1 Growth Attributes of A. Alternata -- 3.2 Grey Relational Generating, Coefficients and Grades -- 3.3 Performance Evaluation of Selected Isolates -- 4 Discussion and Conclusion -- References -- Decision Making for Multi-Items Inventory Models -- 1 Introduction -- 2 Notations and Assumptions -- 2.1 Assumptions -- 2.2 Notations -- 3 Mathematical Model -- 4 Numerical Example and Comparison Study -- 5 Conclusion -- References -- Modeling Australian Twin Data Using Generalized Lindley Shared Frailty Models -- 1 Introduction -- 2 Reversed Hazard Rate -- 3 General Shared Frailty Model -- 4 Generalized Lindley Frailty Model -- 5 Dependence Measure -- 6 Baseline Distributions -- 6.1 Modified Inverse Weibull Distribution -- 6.2 Generalized Rayleigh Distribution -- 7 Proposed Models -- 8 Statistical Properties -- 8.1 Bivariate Density Function -- 8.2 Bivariate Survival Function -- 8.3 Hazard Gradient Function -- 8.4 Conditional Probability Measure. 8.5 Cross-ratio Function -- 9 Likelihood Design and Bayesian Paradigm -- 10 Simulation Study -- 11 Analysis of Australian Twin Data -- 12 Conclusions -- References -- Ultimate Ruin Probability for Benktander Gibrat Risk Model -- 1 Introduction -- 2 Risk Model -- 3 Laplace Transformation -- 4 Ultimate Ruin Probability for BG Distribution -- 5 Calculation of Ultimate Ruin Probability -- 6 Conclusions -- References -- Test of Homogeneity of Scale Parameters Based on Function of Sample Quasi Ranges -- 1 Introduction -- 2 Proposed Test Procedure -- 3 Calculation of Critical Points for Some Specific Distributions: Simulation Method -- 3.1 Critical Points for Standard Exponential, Standard Logistic and Standard Uniform Distributions -- 4 Simultaneous One-Sided Confidence Intervals (SOCI's) of the Proposed Test -- 4.1 Simulated Example to Compute Test Statistic and SOCIs -- 5 Power of the Proposed Test -- 6 Conclusion -- References -- A Bayesian Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent Randomization Method for SMART Designs -- 1 Introduction -- 2 Methods -- 2.1 Overview of the SMART Design -- 2.2 Randomization Probability Using Q-Learning-Based Optimal Decisions -- 2.3 Covariate-Balanced Randomization Probability According to the Prognostic Score for SMART Designs -- 2.4 Response-Adaptive Randomization Probability Based on Outcomes of Previous Groups -- 2.5 Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent (RCQ) Randomization Method -- 3 Simulations Models and Assessment Measures -- 3.1 Simulation Models -- 3.2 Assessment Measures -- 3.3 Simulation Results -- 4 Discussion -- References -- An Introduction to Bayesian Inference for Finite Population Characteristics -- 1 Introduction -- 2 Normal Distribution -- 3 Regression -- 4 Dirichlet Process -- 5 Multiple Regression with Post-stratification. 6 Categorical Data -- 7 Summary and Discussion -- References -- Reliability Measures of Repairable Systems with Arrival Time of Server -- 1 Introduction -- 2 Literature Review -- 3 Some Fundamentals -- 3.1 Reliability -- 3.2 Mean Time to System Failure (MTSF) -- 3.3 Steady-State Availability -- 3.4 Redundancy -- 3.5 Semi-Markov Process -- 3.6 Regenerative Point Process -- 4 Common Notations -- 5 Reliability Measures of Repairable Systems -- 5.1 MTSF and Availability of a Single Unit System with Arrival Time of the Server -- 5.2 MTSF and Availability of a Two-Unit Cold Standby System with Arrival Time of the Server -- 5.3 MTSF and Availability of a Two-Unit Parallel System with Arrival Time of the Server -- 6 Discussion and Conclusion -- References -- Stress-strength Reliability Estimation for Multi-component System Based on Upper Record Values Under New Weibull-Pareto Distribution -- 1 Introduction -- 2 System Reliability -- 3 Maximum Likelihood Estimators (MLE) of Parameters -- 4 Likelihood Ratio (LR) Test for Equality of Scale Parameters -- 5 Estimation of Rs,k Using Maximum Likelihood and Bayesian Methods -- 6 Simulation Study -- 7 Real Data Analysis -- 8 Summary and Conclusions -- References -- Record Values and Associated Inference on Muth Distribution -- 1 Introduction -- 2 Survival Function, Joint and Conditional Densities, and Moments of Upper Records from Muth Distribution -- 3 Parameter Estimation Based on Upper Records Using Moment, Likelihood, and Bayesian Approaches -- 3.1 Moment Estimation of α -- 3.2 Maximum Likelihood Estimation -- 3.3 Bayesian Estimation -- 4 Numerical Illustration -- 5 Real-life Application -- 6 Prediction of Future Records -- 6.1 Frequentist Approach -- 6.2 Bayesian Approach -- 7 Concluding Remarks -- References -- Statistical Linear Calibration in Data with Measurement Errors -- 1 Introduction. 2 Development of Calibration Estimators -- 3 Performance Properties -- 3.1 Large Sample Asymptotic Bias (LSAB) -- 3.2 Large Sample Asymptotic Variance (LSAV) -- 4 An Example -- 5 Conclusions -- References. |
| Record Nr. | UNISA-996549467303316 |
| Gateway East, Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra
| Applied statistical methods : ISGES 2020, Pune, India, January 2-4 / / edited by David D. Hanagal, Raosaheb V. Latpate, and Girish Chandra |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (318 pages) |
| Disciplina | 519.54 |
| Collana | Springer Proceedings in Mathematics and Statistics |
| Soggetto topico |
Mathematical statistics
Estadística matemàtica |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
981-16-7931-2
981-16-7932-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Obituary -- Contents -- Editors and Contributors -- Bayesian Order-Restricted Inference of Multinomial Counts from Small Areas -- 1 Introduction -- 2 Multinomial Dirichlet Models -- 2.1 Model Without Order Restriction (M1) -- 2.2 Model with Order Restrictions (M2) -- 3 Computations -- 3.1 Sampling θ in M2 -- 3.2 Gibbs Sampling for µ and τ -- 4 Application to BMI -- 4.1 Body Mass Index -- 4.2 MCMC Convergence -- 4.3 Model Comparison -- 5 Bayesian Diagnostics -- 6 Conclusion -- 7 Appendix -- 7.1 Details of Gibbs Sampling for µ and τ -- 7.2 Model Comparison -- References -- A Hierarchical Bayesian Beta-Binomial Model for Sub-areas -- 1 Introduction -- 2 Hierarchical Bayesian Small Area Models -- 2.1 A One-Fold Beta-Binomial Model -- 2.2 A Two-Fold Beta-Binomial Model -- 3 Computation -- 3.1 Approximation Method -- 3.2 Exact Method -- 4 Numerical Example -- 4.1 Nepal Living Standards Survey II -- 4.2 Numerical Comparison -- 5 Conclusion and Future Work -- Appendix A Some Details about Approximation of π(µi |τ) -- Appendix B Propriety of the One-Fold Model -- References -- Hierarchical Bayes Inference from Survey-Weighted Small Domain Proportions -- 1 Introduction -- 2 Hierarchical Bayesian Framework -- 3 Application -- 4 Concluding Remarks -- References -- Efficiency of Ranked Set Sampling Design in Goodness of Fit Tests for Cauchy Distribution -- 1 Introduction -- 2 Goodness of Fit Test for Cauchy Distribution -- 3 Power Comparison -- 4 Conclusion -- References -- Fuzzy Supply Chain Newsboy Problem Under Lognormal Distributed Demand for Bakery Products -- 1 Introduction -- 2 Preliminary Definitions and Mathematical Model -- 2.1 Notations and Assumptions -- 2.2 Mathematical Model -- 3 Numerical Case Study -- 4 Results and Discussion -- 5 Conclusions -- References.
Probabilistic Supply Chain Models with Partial Backlogging for Deteriorating Items -- 1 Introduction -- 2 Mathematical Model -- 2.1 Preliminaries -- 3 Genetic Algorithm -- 4 Numerical Example -- 5 Sensitivity Analysis -- 6 Managerial Implications -- 7 Conclusions -- References -- The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Prediction -- 1 Introduction -- 2 Evolution of Dynamic Gaussian Process Model -- 2.1 Basic Gaussian Process Model -- 2.2 Dynamic Gaussian Process Model -- 2.3 Generalizations for Big Data -- 3 Application: Malaria Vaccination Coverage -- 4 Concluding Remarks -- References -- Grey Relational Analysis for the Selection of Potential Isolates of Alternaria Alternata of Poplar -- 1 Introduction -- 2 Material and Methods -- 2.1 Survey and Collection of Alternaria Isolates -- 2.2 GRA for Selection of Potent Isolates -- 3 Results -- 3.1 Growth Attributes of A. Alternata -- 3.2 Grey Relational Generating, Coefficients and Grades -- 3.3 Performance Evaluation of Selected Isolates -- 4 Discussion and Conclusion -- References -- Decision Making for Multi-Items Inventory Models -- 1 Introduction -- 2 Notations and Assumptions -- 2.1 Assumptions -- 2.2 Notations -- 3 Mathematical Model -- 4 Numerical Example and Comparison Study -- 5 Conclusion -- References -- Modeling Australian Twin Data Using Generalized Lindley Shared Frailty Models -- 1 Introduction -- 2 Reversed Hazard Rate -- 3 General Shared Frailty Model -- 4 Generalized Lindley Frailty Model -- 5 Dependence Measure -- 6 Baseline Distributions -- 6.1 Modified Inverse Weibull Distribution -- 6.2 Generalized Rayleigh Distribution -- 7 Proposed Models -- 8 Statistical Properties -- 8.1 Bivariate Density Function -- 8.2 Bivariate Survival Function -- 8.3 Hazard Gradient Function -- 8.4 Conditional Probability Measure. 8.5 Cross-ratio Function -- 9 Likelihood Design and Bayesian Paradigm -- 10 Simulation Study -- 11 Analysis of Australian Twin Data -- 12 Conclusions -- References -- Ultimate Ruin Probability for Benktander Gibrat Risk Model -- 1 Introduction -- 2 Risk Model -- 3 Laplace Transformation -- 4 Ultimate Ruin Probability for BG Distribution -- 5 Calculation of Ultimate Ruin Probability -- 6 Conclusions -- References -- Test of Homogeneity of Scale Parameters Based on Function of Sample Quasi Ranges -- 1 Introduction -- 2 Proposed Test Procedure -- 3 Calculation of Critical Points for Some Specific Distributions: Simulation Method -- 3.1 Critical Points for Standard Exponential, Standard Logistic and Standard Uniform Distributions -- 4 Simultaneous One-Sided Confidence Intervals (SOCI's) of the Proposed Test -- 4.1 Simulated Example to Compute Test Statistic and SOCIs -- 5 Power of the Proposed Test -- 6 Conclusion -- References -- A Bayesian Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent Randomization Method for SMART Designs -- 1 Introduction -- 2 Methods -- 2.1 Overview of the SMART Design -- 2.2 Randomization Probability Using Q-Learning-Based Optimal Decisions -- 2.3 Covariate-Balanced Randomization Probability According to the Prognostic Score for SMART Designs -- 2.4 Response-Adaptive Randomization Probability Based on Outcomes of Previous Groups -- 2.5 Response-Adaptive, Covariate-Balanced and Q-Learning-Decision-Consistent (RCQ) Randomization Method -- 3 Simulations Models and Assessment Measures -- 3.1 Simulation Models -- 3.2 Assessment Measures -- 3.3 Simulation Results -- 4 Discussion -- References -- An Introduction to Bayesian Inference for Finite Population Characteristics -- 1 Introduction -- 2 Normal Distribution -- 3 Regression -- 4 Dirichlet Process -- 5 Multiple Regression with Post-stratification. 6 Categorical Data -- 7 Summary and Discussion -- References -- Reliability Measures of Repairable Systems with Arrival Time of Server -- 1 Introduction -- 2 Literature Review -- 3 Some Fundamentals -- 3.1 Reliability -- 3.2 Mean Time to System Failure (MTSF) -- 3.3 Steady-State Availability -- 3.4 Redundancy -- 3.5 Semi-Markov Process -- 3.6 Regenerative Point Process -- 4 Common Notations -- 5 Reliability Measures of Repairable Systems -- 5.1 MTSF and Availability of a Single Unit System with Arrival Time of the Server -- 5.2 MTSF and Availability of a Two-Unit Cold Standby System with Arrival Time of the Server -- 5.3 MTSF and Availability of a Two-Unit Parallel System with Arrival Time of the Server -- 6 Discussion and Conclusion -- References -- Stress-strength Reliability Estimation for Multi-component System Based on Upper Record Values Under New Weibull-Pareto Distribution -- 1 Introduction -- 2 System Reliability -- 3 Maximum Likelihood Estimators (MLE) of Parameters -- 4 Likelihood Ratio (LR) Test for Equality of Scale Parameters -- 5 Estimation of Rs,k Using Maximum Likelihood and Bayesian Methods -- 6 Simulation Study -- 7 Real Data Analysis -- 8 Summary and Conclusions -- References -- Record Values and Associated Inference on Muth Distribution -- 1 Introduction -- 2 Survival Function, Joint and Conditional Densities, and Moments of Upper Records from Muth Distribution -- 3 Parameter Estimation Based on Upper Records Using Moment, Likelihood, and Bayesian Approaches -- 3.1 Moment Estimation of α -- 3.2 Maximum Likelihood Estimation -- 3.3 Bayesian Estimation -- 4 Numerical Illustration -- 5 Real-life Application -- 6 Prediction of Future Records -- 6.1 Frequentist Approach -- 6.2 Bayesian Approach -- 7 Concluding Remarks -- References -- Statistical Linear Calibration in Data with Measurement Errors -- 1 Introduction. 2 Development of Calibration Estimators -- 3 Performance Properties -- 3.1 Large Sample Asymptotic Bias (LSAB) -- 3.2 Large Sample Asymptotic Variance (LSAV) -- 4 An Example -- 5 Conclusions -- References. |
| Record Nr. | UNINA-9910743343603321 |
| Gateway East, Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical Methods and Applications in Forestry and Environmental Sciences [[electronic resource] /] / edited by Girish Chandra, Raman Nautiyal, Hukum Chandra
| Statistical Methods and Applications in Forestry and Environmental Sciences [[electronic resource] /] / edited by Girish Chandra, Raman Nautiyal, Hukum Chandra |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XII, 288 p.) |
| Disciplina | 634.9015192 |
| Collana | Forum for Interdisciplinary Mathematics |
| Soggetto topico |
Statistics
Forestry Big data Statistics for Life Sciences, Medicine, Health Sciences Statistics for Business, Management, Economics, Finance, Insurance Big Data/Analytics |
| ISBN | 981-15-1476-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Measurement, Data and Statistics: A Historical Voyage in Indian Forestry -- Chapter 2. National Forest Inventory in India: Developments Towards a New Design to Meet Emerging Challenges -- Chapter 3. Internet of Things in Forestry and Environmental Sciences -- Chapter 4. Inverse Adaptive Stratified Random Sampling -- Chapter 5. Improved Nonparametric Estimation Using Partially Ordered Sets -- Chapter 6. Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling -- Chapter 7. Calibration Approach Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling -- Chapter 8. A Joint Calibration Estimator of Population Total Under Entropy Distance Function Based on Dual Frame Surveys -- Chapter 9. Fusing Classical Theories and Biomechanics Into Forest Modelling -- Chapter 10. Statistical Multivariate Methods for Decision Making in Classification of Water Quality Data and Management of Water Resources -- Chapter 11. Investigating Selection Criteria of Constrained Cluster Analysis: Applications in Forestry -- Chapter 12. Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species -- Chapter 13. Some Investigations on Designs for Mixture Experiments with Process Variable -- Chapter 14. Development in Copula Applications in Forestry and Environmental Sciences -- Chapter 15. Forest Cover Type Prediction Using Model Averaging -- Chapter 16. Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses -- Chapter 17. Small Area Estimation for Total Basal Cover in the State of Maharashtra, India -- Chapter 18. Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India -- Chapter 19. Exploration of Metagenomics Tools for Analysis of Forest Soil Microbial Diversity and its Annotation -- Chapter 20. Integrated Survey Scheme to Capture Forestry Related Data in Bangladesh: Beyond the Traditional Approach. |
| Record Nr. | UNISA-996418197703316 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Statistical Methods and Applications in Forestry and Environmental Sciences [[electronic resource] /] / edited by Girish Chandra, Raman Nautiyal, Hukum Chandra
| Statistical Methods and Applications in Forestry and Environmental Sciences [[electronic resource] /] / edited by Girish Chandra, Raman Nautiyal, Hukum Chandra |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XII, 288 p.) |
| Disciplina | 634.9015192 |
| Collana | Forum for Interdisciplinary Mathematics |
| Soggetto topico |
Statistics
Forestry Big data Statistics for Life Sciences, Medicine, Health Sciences Statistics for Business, Management, Economics, Finance, Insurance Big Data/Analytics |
| ISBN | 981-15-1476-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Measurement, Data and Statistics: A Historical Voyage in Indian Forestry -- Chapter 2. National Forest Inventory in India: Developments Towards a New Design to Meet Emerging Challenges -- Chapter 3. Internet of Things in Forestry and Environmental Sciences -- Chapter 4. Inverse Adaptive Stratified Random Sampling -- Chapter 5. Improved Nonparametric Estimation Using Partially Ordered Sets -- Chapter 6. Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling -- Chapter 7. Calibration Approach Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling -- Chapter 8. A Joint Calibration Estimator of Population Total Under Entropy Distance Function Based on Dual Frame Surveys -- Chapter 9. Fusing Classical Theories and Biomechanics Into Forest Modelling -- Chapter 10. Statistical Multivariate Methods for Decision Making in Classification of Water Quality Data and Management of Water Resources -- Chapter 11. Investigating Selection Criteria of Constrained Cluster Analysis: Applications in Forestry -- Chapter 12. Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species -- Chapter 13. Some Investigations on Designs for Mixture Experiments with Process Variable -- Chapter 14. Development in Copula Applications in Forestry and Environmental Sciences -- Chapter 15. Forest Cover Type Prediction Using Model Averaging -- Chapter 16. Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses -- Chapter 17. Small Area Estimation for Total Basal Cover in the State of Maharashtra, India -- Chapter 18. Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India -- Chapter 19. Exploration of Metagenomics Tools for Analysis of Forest Soil Microbial Diversity and its Annotation -- Chapter 20. Integrated Survey Scheme to Capture Forestry Related Data in Bangladesh: Beyond the Traditional Approach. |
| Record Nr. | UNINA-9910483831403321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||