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assignmentutor-lab™ 为您的留学生涯保驾护航 在代写贝叶斯统计方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写贝叶斯统计代写方面经验极为丰富，各种代写贝叶斯统计相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|贝叶斯统计代写Bayesian statistics代考|LAWLIKENESS

In Professor Goodman’s view, as I understand it, the Hempelian (satisfaction) criterion of confirmation is sound, provided that it is restricted to lawlike hypotheses. ${ }^3$ While, informally, one might characterize as ‘law-like’ those hypotheses which are confirmed by their Hempelian instances, an independent criterion must be provided. Roughly, Goodman proposes to measure lawlikeness by the entrenchment of the predicates involved. Entrenchment reflects the frequency with which the extension of a predicate has been projected or has figured in ‘successful’ inductions. (It is in this form, Goodman holds, that our past inductive experience bears on our present practice.) I must assume in what follows that at least the main outlines of Goodman’s entrenchment theory are familiar to the reader. ${ }^4$

My own view is that entrenchment per se has but little to do with confirmability or lawlikeness. What matters is, not that the predicates of an hypothesis have figured in successful laws or theories, but that there be theoretically grounded relations between the predicates which the hypothesis links. And that is only to say the residual background theory provides some prior presumption in favor of the hypothesis.

Whatever else it is intended to do, the entrenchment theory is aimed at driving a wedge between the grue hypothesis and its presumably nonpathological counterpart, ‘All emeralds are green’. While ‘green’ and other ordinary color terms have figured in many a good empirical law, ‘grue’ has not. Yet, it is not hard to cook up cases, given the right sort of background knowledge, where a gruelike hypothesis is both more confirmable and enjoys higher prior probability.

Consider a twofold classification of chips in an um: they are circles or squares, black or white. ‘Blite’ applies to black squares or white circles. Assume all $2^{2 N}$ states of the population of $N$ chips equiprobable. Then I claim the hypothesis $K$ that all chips are blite is more confirmable than the hypothesis $H$ that all circular chips are black. Here ‘more confirmable’ means ‘better confirmed by a conforming outcome’. Suppose that a random sample of one yields a black square, an outcome which conforms to both hypotheses. It can be shown this outcome is more probable on $K$ than on $H$, and hence,better confirms $K$. The case $N=2$ is shown in Figure 1. Let $X$ be the outcome in question (drawing a black square). We have $P(X / K)=$ $(1+1 / 2+1 / 2+0) / 4=1 / 2$, while $P(X / H)=(1+1 / 2+1 / 2+1 / 2+1 / 2+0+0$ $+0+0) / 9=1 / 3$, there being 9 states in which $H$ holds $(6-10,13-16)$ and just 4 in which $K$ holds ( $1-3,6$ in Figure 1 ).

## 统计代写|贝叶斯统计代写Bayesian statistics代考|CONCLUSION

Professor Hempel has insisted from the start that his definition of confirmation in terms of satisfaction applies only to ‘theoretically barren’ contexts where background knowledge is lacking. If that proviso is respected, we can no longer claim, for example, that finding white crows actually disconfirms the raven hypothesis, for there we were appealing to the knowledge that crows and ravens are biologically related species. On the other hand, if we suppressed our belief that emeralds in all parts of space-time are the same color, it would be hard to see what is paradoxical about the alleged confirmation of the grue hypothesis by green emeralds. Be that as it may, let us consider Hempel’s restriction.

It can be shown ${ }^7$ that if all compositions of a doubly dichotomized population are equiprobable, then all three of the conforming types, $A B$ ‘s, non- $A B$ ‘s, and non- $A$ non- $B$ ‘s, afford ‘All $A$ are $B$ ‘ equal confirmation (in a probability sense). For then, as is evident from symmetry, all three types are equiprobable conditional on the hypothesis in question. If we equate then a ‘barren’ context with a uniform distribution over worlds (state descriptions), we can affirm a strong form of Hempel’s claim that, appearances notwithstanding, non- $A$ ‘s are genuinely confirmatory instances of ‘All $A$ are $B$ ‘. Without some such condition, however, we cannot even affirm that $A B$ ‘s are confirmatory.

On the other hand, if by a ‘barren’ context is meant one in which no pertinent background knowledge at all is available, I would be inclined to doubt whether such contexts exist. The very structure of human perceptual systems, with their built-in tendencies to group objects, select given features, or reidentify features, may already be tantamount to background knowledge. Certainly the use of terms which denote natural kinds already presupposes a good deal. Even if a clear meaning could be given to the conception of inductive inference in a theoretical vacuum, I do not see how anything could be concluded about confirmation. In short, the real issue between Hempel and the Bayesians, as I see it, is whether anything at all can be inferred about confirmation on the basis of the semantical relation of satisfaction alone, beyond what I have already noted: that conformable stoogian observations are confirming. The significance of these reflections for the traditional problem of ‘justifying induction’ will be taken up next.

# 假设检验代写

## 统计代写|贝叶斯统计代写Bayesian statistics代考|CONCLUSION

Hempel 教授从一开始就坚持认为，他对满意度的确认定义仅适用于缺乏背景知识的“理论上贫瘠”的环境。如果遵守该附带条件，我们就不能再声称，例如，发现白乌鸦实际上否定了乌鸦的假设，因为在那里我们呼吁乌鸦和乌鸦是生物学相关物种的知识。另一方面，如果我们不相信时空所有部分的祖母绿都是相同颜色的，那么就很难看出所谓的绿祖母绿证实了绿色假设的自相矛盾之处。尽管如此，让我们考虑一下 Hempel 的限制。

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师