Logo

Randomness and Optimal Estimation in Data Sampling

Small book cover: Randomness and Optimal Estimation in Data Sampling

Randomness and Optimal Estimation in Data Sampling
by

Publisher: American Research Press
ISBN/ASIN: 1931233683
Number of pages: 63

Description:
The purpose of this book is to postulate some theories and test them numerically. Estimation is often a difficult task and it has wide application in social sciences and financial market. This book has been designed for graduate students and researchers who are active in the area of estimation and data sampling applied in financial survey modeling and applied statistics.

Download or read it online for free here:
Download link
(610KB, PDF)

Similar books

Book cover: Public Debt, Inequality, and PowerPublic Debt, Inequality, and Power
by - University of California Press
This book is the first comprehensive historical analysis of public debt ownership in the United States. It reveals that ownership of federal bonds has been increasingly concentrated in the hands of the 1 percent over the last three decades.
(3762 views)
Book cover: PhynancePhynance
by - arXiv
These are the lecture notes for an advanced Ph.D. level course, primarily focused on an introduction to stochastic calculus and derivative pricing with various stochastic computations recast in the language of path integral, which is used in physics.
(6215 views)
Book cover: Financial Strategy for Public ManagersFinancial Strategy for Public Managers
by - The Rebus Foundation
This is a new generation textbook for financial management in the public sector. It offers a thorough, applied, and concise introduction to the essential financial concepts and analytical tools that today's effective public servants need to know.
(3042 views)
Book cover: Portfolio Theory and Financial AnalysesPortfolio Theory and Financial Analyses
by - BookBoon
The book evaluates Modern Portfolio Theory for future study. We learn why anybody with the software and a reasonable financial education can model portfolios. We learn why investors and not their computers should always interpret their results.
(8603 views)