Analysis of Poverty Data by Small Area Estimation, Pratesi
Автор: Currell Graham Название: Scientific Data Analysis ISBN: 0198712545 ISBN-13(EAN): 9780198712541 Издательство: Oxford Academ Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on the author`s extensive experience of supporting students undertaking projects, Scientific Data Analysis is a guide for any science undergraduate or beginning graduate who needs to analyse their own data, and wants a clear, step-by-step description of how to carry out their analysis in a robust, error-free way.
Автор: Guerrero, Hector Название: Excel data analysis ISBN: 3030012786 ISBN-13(EAN): 9783030012786 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive and readable introduction to modern business and data analytics.
Автор: Azizur Rahman, Ann Harding Название: Small Area Estimation and Microsimulation Modeling ISBN: 036726126X ISBN-13(EAN): 9780367261269 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book gathers information on the theories, applications, advantages, and limitations of all the small area estimation methodologies. It covers direct small area estimation methods, indirect statistical approaches, including empirical best linear unbiased prediction, empirical Bayes and hierarchical Bayes estimation methods.
Автор: Morales, Domingo Esteban, Maria Dolores Perez, Agustin Hobza, Tomas Название: Course on small area estimation and mixed models ISBN: 3030637565 ISBN-13(EAN): 9783030637569 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
Описание: This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation.
Автор: J. N. K. Rao,Isabel Molina Название: Small Area Estimation ISBN: 1118735781 ISBN-13(EAN): 9781118735787 Издательство: Wiley Рейтинг: Цена: 14565.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Praise for the First Edition "This pioneering work, in which Rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic. I believe that it has the potential to turn small area estimation. into a larger area of importance to both researchers and practitioners.
Описание: of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl` . , X , usually depends in n a complicated manner on the cyclic frequency). , are approximated by values of a certain sufficiently simple function 1 = 1
Автор: Werner Schiehlen; Walter Wedig Название: Analysis and Estimation of Stochastic Mechanical Systems ISBN: 3211820582 ISBN-13(EAN): 9783211820582 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The main aspects of the course are random vibrations of discrete and continuous systems, analysis of nonlinear and parametric systems, stochastic modelling of fatigue damage, parameter estimation and identification with applications to vehicle road systems and process simulations by means of autoregressive models.
Автор: Sivan Toledo Название: Location Estimation from the Ground Up ISBN: 1611976286 ISBN-13(EAN): 9781611976281 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 8715.00 р. Наличие на складе: Нет в наличии.
Описание: The location of an object can often be determined from indirect measurements using a process called estimation. This book explains the mathematical formulation of location-estimation problems and the statistical properties of these mathematical models. It also presents algorithms that are used to resolve these models to obtain location estimates, including the simplest linear models, nonlinear models (location estimation using satellite navigation systems and estimation of the signal arrival time from those satellites), dynamical systems (estimation of an entire path taken by a vehicle), and models with integer ambiguities (GPS location estimation that is centimeter-level accurate).Location Estimation from the Ground Up clearly presents analytic and algorithmic topics not covered in other books, including simple algorithms for Kalman filtering and smoothing, the solution of separable nonlinear optimization problems, estimation with integer ambiguities, and the implicit-function approach to estimating covariance matrices when the estimator is a minimizer or maximizer. It takes a unified approach to estimation while highlighting the differences between classes of estimation problems. The only book on estimation written for math and computer science students and graduates, it includes problems at the end of each chapter, many with solutions, to help readers deepen their understanding of the material and guide them through small programming projects that apply theory and algorithms to the solution of real-world location-estimation problems.The book’s core audience consists of engineers, including software engineers and algorithm developers, and graduate students who work on location-estimation projects and who need help translating the theory into algorithms, code, and deep understanding of the problem in front of them. Instructors in mathematics, computer science, and engineering may also find the book of interest as a primary or supplementary text for courses in location estimation and navigation.
Автор: Rahman Название: Small Area Estimation And Microsimu ISBN: 1482260727 ISBN-13(EAN): 9781482260724 Издательство: Taylor&Francis Рейтинг: Цена: 14086.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book gathers information on the theories, applications, advantages, and limitations of all the small area estimation methodologies. It covers direct small area estimation methods, indirect statistical approaches, including empirical best linear unbiased prediction, empirical Bayes and hierarchical Bayes estimation methods.
Описание: In 2013, the World Bank Group announced two goals that would guide its operations worldwide. First is the eradication of chronic extreme poverty bringing the number of extremely poor people, defined as those living on less than 1.25 purchasing power parity (PPP)–adjusted dollars a day, to less than 3 percent of the world’s population by 2030.The second is the boosting of shared prosperity, defined as promoting the growth of per capita real income of the poorest 40 percent of the population in each country.In 2015, United Nations member nations agreed in New York to a set of post- 2015 Sustainable Development Goals (SDGs), the first and foremost of which is the eradication of extreme poverty everywhere, in all its forms. Both the language and the spirit of the SDG objective reflect the growing acceptance of the idea that poverty is a multidimensional concept that reflects multiple deprivations in various aspects of well-being. That said, there is much less agreement on the best ways in which those deprivations should be measured, and on whether or how information on them should be aggregated. Monitoring Global Poverty: Report of the Commission on Global Poverty advises the World Bank on the measurement and monitoring of global poverty in two areas:What should be the interpretation of the definition of extreme poverty, set in 2015 in PPP-adjusted dollars a day per person?What choices should the Bank make regarding complementary monetary and nonmonetary poverty measures to be tracked and made available to policy makers?The World Bank plays an important role in shaping the global debate on combating poverty, and the indicators and data that the Bank collates and makes available shape opinion and actual policies in client countries, and, to a certain extent, in all countries. How we answer the aforementioned questions can therefore have a major influence on the global economy.
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