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• 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

## 数学代写|信息论作业代写information theory代考|Reflections on the Measurement of Information

The measurement of information and its unit of measure are relevant only over the epistemological space, where the rise of qualitative disagreements establishes some domain of subjective phenomenon such that order-ranking inconsistency may arise among cognitive agents. To the source agent the need for measurement is to determine the relevant and appropriate channel capacity for the transmission of the signal disposition that carries the characteristic disposition of a variety or a categorial variety. The required channel capacity will depend on the size of the signal disposition which is equipped with an encoding operator that must be decoded for understanding and meaning. The decoding of the signal disposition reveals the underlying structure of the characteristic disposition and the identity of the associated variety. The information contained in the decoded message at the destination is said to be perfectly transmitted if it is completely isomorphic to the information contained in the encoded message from the source. In this way $9 k^{\sigma}=9 \kappa^{\delta}$ and the information from the source becomes the information at the destination and the communication is perfectly synchronized. The message sent and the message received are said to be information isomorphic. The conditions for the information isomorphism, among other things, will depend on the relational structure of encoding operator $\varnothing$ and decoding operator $\mathscr{8}$ given the transmission mechanism. An example may be found in all languages such that there exists a translation function operator $h$ that maps the decoding operator onto the encoding operator with $h(\mathscr{D})=\varnothing$ and $\mathscr{D}=h^{-1}(\varnothing)$. An examples of transmission mechanism in the case of languages are voice and writing. Knowledge production requires some degree of information isomorphism between ontological encoding and epistemological decoding.

A number of questions tend to arise concerning the communication activities of cognitive agents over the epistemological space. Given a channel capacity, what is the size of an optimal signal disposition that may be sent through both a noiseless or a noisy channel to a destination and what is the associated risk of transmission error? Given a signal disposition of defined variety, what is either an optimal noiseless or noisy channel capacity required to transmit it with minimal chance of transmission error? What does it mean to speak of transmission error or risk in both cases? Are the transmission errors and risks defined by the concept and measure of probability and does probability define the conditions of uncertainty and hence can one use probability to define the concept of uncertainty and vice versa?

## 数学代写|信息论作业代写information theory代考|The Subject Matters of Info-statics and Info-dynamics

The theory of info-statics is a branch in the theory of knowledge concerned with definition of the concept of information that will establish the information phenomenon and its content, measurement and communication. Furthermore, the theory of info-statics must deal with the nature of qualitative and quantitative dispositions of information and how they relate to universal objects to define their identities, meaning, distinction, similarities and differences at any point of time. Under these conditions, the theory of info-statics must provide the required framework and conditions to form categories of varieties at any time point. In other words, it must include a category theory that defines the conditions of its formation and analysis through categorial analytics. The category formation may be constructed through the methods and techniques of fuzzy decomposition of universal existence of matter and energy. In this way, the theory over the epistemological space must deal with the information properties that make it possible for comparative analytics, order analytics and decision-choice analytics. Over the ontological space, the theory of info-statics must deal with conditions of existence and its observability over the epistemological space in time. Furthermore, the theory of info-statics must provide an understanding of the relational structure among matter, energy and information under similarities and differences which establish identities of varieties and categorial varieties of the collection of universal phenomena $\phi \in \Phi$ and the collection of the corresponding elements $\omega \in \Phi$ at a defined time position. The theory of info-statics must also establish a sequential structure at any time point where the theory presents conditions in a manner that allows the identification of the primary categories on the basis of which other categories of knowing may be sequentially derived to define the enveloping of qualitative and quantitative dispositions with neutrality of time. In other words, the theory info-statics must establish the initial necessary and sufficient conditions for one to know if a change of a variety has occurred with different time identities.

# 信息论代写

## 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。

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