Applied Statistics in Social Sciences
This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics different financial problems and other scenarios in which these recently developed statistical models have been applied in recent years. They include actuarial statistics stochastic frontier analysis duration models population geography income and wealth distribution physical economics and tourism among others. Each distribution is dealt with in a separate chapter along with descriptions of all possible applications. The authors also provide a detailed analysis of the proposed probabilistic families discussing their relationship with existing models statistical properties analyzing their strengths and weaknesses similarities and differences different estimation methods along with comments on possible applications and extensions. Simulation methods are given for most of the models presented. Many of the probabilistic models shown together with their applications in the fields mentioned above are a result of numerous research articles published by the authors and other researchers mainly based on classical formulations which have been the foundations of more general models. This volume contains an extensive updated bibliography from journals and books on statistics mathematics economics actuarial sciences and computer science. This book is an essential manual for researchers professionals and in general for graduate students in computer science engineering bioinformatics statistics and mathematics since the concise writing style makes the book accessible to a broad audience. | Applied Statistics in Social Sciences
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Details:Applied Statistics in Social Sciences
This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics different financial problems and other scenarios in which these recently developed statistical models have been applied in recent years. They include actuarial statistics stochastic frontier analysis duration models population geography income and wealth distribution physical economics and tourism among others. Each distribution is dealt with in a separate chapter along with descriptions of all possible applications. The authors also provide a detailed analysis of the proposed probabilistic families discussing their relationship with existing models statistical properties analyzing their strengths and weaknesses similarities and differences different estimation methods along with comments on possible applications and extensions. Simulation methods are given for most of the models presented. Many of the probabilistic models shown together with their applications in the fields mentioned above are a result of numerous research articles published by the authors and other researchers mainly based on classical formulations which have been the foundations of more general models. This volume contains an extensive updated bibliography from journals and books on statistics mathematics economics actuarial sciences and computer science. This book is an essential manual for researchers professionals and in general for graduate students in computer science engineering bioinformatics statistics and mathematics since the concise writing style makes the book accessible to a broad audience. | Applied Statistics in Social Sciences
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Product Description
This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics different financial problems and other scenarios in which these recently developed statistical models have been applied in recent years. They include actuarial statistics stochastic frontier analysis duration models population geography income and wealth distribution physical economics and tourism among others. Each distribution is dealt with in a separate chapter along with descriptions of all possible applications. The authors also provide a detailed analysis of the proposed probabilistic families discussing their relationship with existing models statistical properties analyzing their strengths and weaknesses similarities and differences different estimation methods along with comments on possible applications and extensions. Simulation methods are given for most of the models presented. Many of the probabilistic models shown together with their applications in the fields mentioned above are a result of numerous research articles published by the authors and other researchers mainly based on classical formulations which have been the foundations of more general models. This volume contains an extensive updated bibliography from journals and books on statistics mathematics economics actuarial sciences and computer science. This book is an essential manual for researchers professionals and in general for graduate students in computer science engineering bioinformatics statistics and mathematics since the concise writing style makes the book accessible to a broad audience. | Applied Statistics in Social Sciences
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