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Unbiased Estimation,.2. In this chapter, we discuss in detail how to derive unbiased estimators and, more importantly, how to find the best unbiased estimators in various situations. Although an unbiased estimator (even the best unbiased estimator if it exists) is not necessarily better than a slightly biased estimator熔岩 发表于 2025-3-25 12:35:51
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Hypothesis Tests, observed ., we test a given hypothesis . : . ∈ . versus . : . ∈ ., where . and . are two disjoint subsets of . and .∪. = .. Notational conventions and basic concepts (such as two types of errors, significance levels, and sizes) given in Example 2.20 and §2.4.2 are used in this chapter.Bumptious 发表于 2025-3-25 22:52:36
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https://doi.org/10.1007/b97553Mathematical Statistics; Statistical Theory; likelihood; Markov chain; Mathematica; mathematical statisti开花期女 发表于 2025-3-26 06:26:39
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Springer Texts in Statisticshttp://image.papertrans.cn/m/image/626590.jpg突袭 发表于 2025-3-26 15:10:33
Fundamentals of Statistics,This chapter discusses some fundamental concepts of mathematical statistics. These concepts are essential for the material in later chapters.斥责 发表于 2025-3-26 18:59:16
Estimation in Parametric Models,In this chapter, we consider point estimation methods in parametric models. One such method, the moment method, has been introduced in §3.5.2. It is assumed in this chapter that the sample . is from a population in a parametric family .={. : . ∈ Θ}, where Θ ⊂ . for a fixed integer . ≥ 1.