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Total Size:
7.5 MB
Info Hash:
2B4207A6CD64ACF5328C9B0369891578B255A603
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Added:
June 12, 2025, 3:34 p.m.
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(Last updated: June 12, 2025, 8:46 p.m.)
| File | Size |
|---|---|
| ['Fang K. Representative Points of Statistical Distributions..Stat. Inference 2025.pdf'] | 0 bytes |
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149.5 GB
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2026-03-01
| Uploaded by vasparvan | Size 149.5 GB | Health [ 4 /15 ] | Added 2026-03-01 |
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387.8 MB
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| Uploaded by derviches70 | Size 387.8 MB | Health [ 4 /3 ] | Added 2023-07-05 |
NOTE
SOURCE: Fang K. Representative Points of Statistical Distributions..Stat. Inference 2025
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COVER
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MEDIAINFO
Textbook in PDF format Statistical simulation has become a cornerstone in statistical research and applications. The aim of Representative Points of Statistical Distributions: Applications in Statistical Inference is to present a comprehensive exploration of various methods for statistical simulation and resampling, focusing on consistency and efficiency. It covers a range of representative points (RPs) – Monte Carlo (MC) RPs, quasi-Monte Carlo (QMC) RPs, and mean square error (MSE) RPs – and their applications, and includes a collection of recent developments in the field. It also explores other types of representative points and the corresponding approximate distributions, and delves into the realm of statistical simulation by exploring the limitations of traditional MC methods and the innovations brought about by the bootstrap method. In addition, the text introduces other kinds of representative points and the corresponding approximate distributions such as QMC and MSE methods
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