连续随机变量

词组短语

continuous random variable

与连续随机变量相关的网络例句 [注：此内容来源于网络，仅供参考]

Events,Operation and Relation of Sets, Classical Probability, Geometrical Probability , Statistical Stability of a Frequency, Axioms of Probability, Conditional Probability, Total Probability Theorem, Bayes' Rule,Independent Events,Independent Repeated Trials, One Dimensional Random Variables, Discrete Random Variables, Distribution Function of a Random Variables , Continuous Random Variables, Normal Distribution, Distribution of a Function of a Random Variable, Multidimensional Random Variables, Joint Distribution Function, Marginal Distribution Function,Discrete Two—Dimensional Random Variables,Continuous Two—Dimensional Random Variables, Independent Random Variables, Distribution of Functions of Random Variables,Expectation,Variance, Covariance, Coefficient of Correlation, Bivariate Normal Distribution, Law of Large Numbers, The Central Limit Theorems, Sample and Population ,Chi—Squared, T and F Distributions , Sampling Distributions , Point Estimation , Interval Estimation , Testing Hypotheses , A Test of Significance for Parameters in a Single Sample From a Normally Distributed Population , A Test of Significance for Parameters in Two Sample From Normally Distributed Populations .

本课程的主要内容：概率的概念与运算、随机变量及其分布、随机变量的数字特征与极限定理、数理统计的基本概念、估计和检验的基本方法，随机事件与概率随机事件、事件的关系与运算、几何概率、统计概率等，条件概率、全概率公式、贝叶斯公式、事件的独立性、二项概率公式，随机变量的概念、离散型随机变量、随机变量的分布函数、连续型随机变量、随机变量函数的分布，多维随机变量及其分布函数、边缘分布函数、随机变量的独立性、二维随机变量函数的分布，数学期望、方差、协方差和相关系数、大数定律、中心极限定理，总体与样本， X 2-分布、 t-分布和 F-分布，统计量及抽样分布，假设检验的基本概念、单个正态总体参数的显著性检验、两个正态总体参数的显著性检验。

As for continuous random variable, the connection of distribution function between random variable and its function -- a new random variable can be obtained first according to the definition of distribution function, then the connection between distribution densities can be obtained by derivation; thus the distribution density is solved.

对于连续型随机变量ξ来说，可由分布函数的定义先求出随机变量ξ和它的函数η=f这个新的随机变量的分布函数之间的联系，然后通过求导，得到密度函数之间的联系，从而求得η的分布密度。

The text introduces the probability of random events and issues of counter-examples; discrete random variables related to the distribution and continuous random variable distribution of counter-examples; independence and related issues in the Phase capacitive on the counter-examples; number of characteristics of the random variable The counter-examples of; parameters estimates and assumptions in the anti-testing case of problems.

该文主要介绍了随机事件及其概率问题中的反例；有关离散型随机变量分布和连续型随机变量分布中的反例问题；独立性与相关性相容性问题中的反例介绍；有关随机变量数字特征的反例探讨；有关参数估计与假设检验中的反例问题。

And then the approach is extended to continuous random variable. The optimal rule of general group decision-making is drawn by the new approach, which turns out to be a generalized weighted majority rule. The weight allocated to a decision-maker should be equal to the information quantity he provides.

鉴于Boltzmann—Shannon熵难以直接用来度量群体决策中信息的变动情况，我们提出了一种对离散随机变量的新的信息度量方法，证明了该信息函数仍然满足等状态时信息量最小这一性质；随后将其推广到了连续随机变量。

That not only could be extended to the continuous random varia- ble,but also the theorem of maximum information measure could be extended to the continuous random variable, which unified the measurement arithmetic of information between distributed random variable and continuous ran- dom variable,and gave two validating models to the information entropy of the continuous random variable in the last.

用公理化的方法，推导出了有限分布列的离散型随机变量的信息量系，不仅将它推广到连续型随机变量，而且将信息量系的最大信息量定理推广到连续型随机变量，统一了离散型和连续型随机变量的信息度量算法。最后利用得出的结论对连续型随机变量信息熵给出两个验证性算例。

As to the risk model with random premium rate, we concerned with discrete random variable, continuous random variable and general random variable. We derive the formula of ruin probability, the extreme during the total duration of negative surplus and the joint distribution of the surplus immediately before ruin and the deficit at ruin.

对于保费率为随机变量的一类风险模型，本文就离散的随机变量、连续的随机变量、一般的随机变量三个方面进行讨论，运用概率方法和风险理论的方法推导出破产概率、末离前最大盈余分布、破产前瞬时盈余与破产赤字的联合分布等精算量分布的一般公式。

The identity and difference in the expressional patterns between distribution functions of discrete random variables and distribution functions of continuous random variables are elaborated,and the main expressional patterns of distribution functions of continuous random variables are summarized,and the derivability of distribution functions of continuous random variables is discussed.

0引言在概率论中，连续型随机变量分布函数的表达形式及其可导性是一难点。其一，离散型随机变量的分布函数有较明显的性质和统一的表达形式，而连续型随机变量，由于其概率密度函数一般为分段函数，根据其分段区间的差异，表达形式差异较大，不容易总结其规律，本文主要比较连续型随机

The discrete random height variable of worn surface is described with continuous random variables by a mathematical method.

建立了磨损表面轮廓数值化基准、用连续随机变量来描述磨损表面轮廓线高度离散随机变量，对磨损表面高度分布作了数理统计分析，研究了载荷、滑动速度及镀层种类对磨损表面几何特性的影响，将数理统计分析结果与镀层的耐磨性作了比较分析，较为完整、深入地描述了磨损表面的几何特性。

This project also obtained several limit theorems for some important dependent random variables and stochastic processes, such as the Strassen law of the iterated logarithm for negatively dependent random variables, strong limit theorems for mixing random vectors in Banach spaces, sample path properties for two-parameter fractional Wiener processes, and so on.

随机环境中的随机变量与随机过程的研究在国内外相当活跃，本项目主要研究它们的极限性质，着重研究了随机风景中随机变量与随机过程的极限性质，主要取得了以下几个结果：首先对简单对称的Kesten-Spitzer随机游动在低阶矩的条件下给出了强逼近，大大减弱了前人要求任意阶矩的条件，然后对独立风景中的一般随机变量给出了强逼近的一般性结果，由此导出在风景和随机变量都只具有低阶矩的条件下的独立但不同分布、混合相依变量的强逼近，在只有弱高于二阶矩的条件下得到了重相对数律和弱收敛；给出了连续时间参数的Brown风景中Brown运动和稳定风景中稳定过程的滞后增量和连续模等精确样本轨道性质；同时给出了一些重要的相依随机变量和过程的若干极限定理，如负相关随机变量的Strassen重对数律、抽象空间上混合相依变量的一些强极限定理成立的充分必要条件、两参数分数Wiener过程的样本轨道性质等。

The notion of sample relative entropy , as a random measure of the deviation of a sequence of nonnegative continuous random sequence from independent random sequence with exponential distribution, is introduced.

利用样本相对熵作为一般非负连续型随机变量序列相对于服从指数分布的独立但不同分布随机变量序列偏差的一种随机性度量，运用鞅理论及分析方法，研究了一类随机变量序列加权和的用不等式表示的极限定理，即强偏差定

与连续随机变量相关的网络解释 [注：此内容来源于网络，仅供参考]

continuous random process：连续随机过程

continuous qurrent 连续电流 | continuous random process 连续随机过程 | continuous random variable 连续随机变量

Continuous random variable：连续型随机变量

另一方面,连续型随机变量 (continuous random variable)可以取某一区间范围内的任意值. 例如,人的身高就是一个连续型随机变量,它可以取在 6 0? 7 2英寸范围内的任一值. 类似的,体重、降雨量、温度等都可看做是连续型随机变量.

Continuous random variable：连续随机变量

continuous lighting 连续照明 | continuous random variable 连续随机变量 | continuous variable 连续性变数

Continuous random variable：连续随机变量 連續性隨機變數

continuous quadrat 连续观察样方 連續樣區 N | continuous random variable 连续随机变量 連續性隨機變數 Y | continuous variation 连续变异 連續變異 Y

bivariate continuous random variable：二维连续型随机变量

joint distribution law 联合分布律 | bivariate continuous random variable 二维连续型随机变量 | joint probability density function 联合概率密度函数

random variable of continuous type：连续型随机变量

random variable 随机变量=>確率変数 | random variable of continuous type 连续型随机变量 | random variation 随机变化,随机变异=>不規則変動

continuous variable programming：连续变量规划,连续型规划

continuous variable optical attenuator 连续可变光衰减器 | continuous variable programming 连续变量规划,连续型规划 | continuous variate 连续随机变量

discontinuous variable：离散型随机变量

discontinuity theory of learning 非连续学习论 | discontinuous variable 离散型随机变量 | discontinuous volume 非连续容量

discrete probability distribution：离散型随机变量的分布

A definition of random variables随机变量的概念 | Discrete probability distribution离散型随机变量的分布 | Continuous probability distribution连续型随机变量的分布

random variable：随机变量

1.随机变量 随机变量(random variable) 指取值不能事先确定的观察结果,通常简称为变量. 随机变量有一个共同的特点就是不能用一个常数来表示,而且理论上讲,每个变量的取值服从特定的概率分布. 随机变量可分为两种类型:离散型变量和连续型变量.