measure theory - Characterisation of point-mass distributions ...
2019年2月8日 · Prove that every measure μ μ on (X,2X) (X, 2 X) is a point-mass distribution. μ(E) =∑x∈E a(x) μ (E) = ∑ x ∈ E a (x) If the set X is at most countable this obvious. We just have to take a(x) = μ({x}) a (x) = μ ({x}), for every x ∈ E x ∈ E and use the countable additivity of the measure to gain the result, since E =∪x∈E{x} E = ∪ x ∈ E {x}.
Mass distribution - Wikipedia
In physics and mechanics, mass distribution is the spatial distribution of mass within a solid body. In principle, it is relevant also for gases or liquids, but on Earth their mass distribution is almost homogeneous. In astronomy mass distribution has decisive influence on the development e.g. of nebulae, stars and planets.
在Workbench中使用结构点单元进行简化计算的方法 - 搜狐
2019年9月25日 · Point Mass的位置选择，支持鼠标拾取，空间坐标定义和远端点关联；Point Mass参数包括总质量，三个方向的质量转动惯量（仅对动力学计算有效），Point Mass依附面的行为和球形区域设置，在计算…
Different interpretations of point mass (degenerate distribution)
2017年5月3日 · In a Probability book by Karr, the point mass (degenerate distribution) is defined as: ϵω(A) ϵ ω (A) = 1A(ω) 1 A (ω) (where 1 1 is the indicator function). Since the LHS is a function of A (for a fixed outcome ω ω), and the RHS is a function of ω ω (for a fixed event A), how can the two functions be equal? What does the equality here represents?
After all, a Keplerian RC corresponds to a delta-function density distribution (point mass), which is the most concentrated mass distribution possible....
概率质量函数 - 维基百科，自由的百科全书
在 机率论 和 统计学 中， 机率质量函数 （probability mass function，简写作 pmf）是 离散随机变数 在各特定取值上的机率 [1]。 有时它也被称为离散密度函数。 机率密度函数通常是定义 离散机率分布 的主要方法，并且此类函数存在于其 定义域 是离散的 标量 变数或 多元随机变数。 机率质量函数 和 机率密度函数 的一个不同之处在于：机率质量函数是对 离散随机变数 定义的，本身代表该值的机率；机率密度函数本身不是机率，只有对连续随机变数的 机率密度函数 必须在某一 …
It is often useful to think about a continuous distribution of mass rather than a collection of discrete points. For example, one might want to know the properties of a slab of rock of a given density without having to count up all the individual atoms in the slab.
Point particle - Wikipedia
A point particle is an appropriate representation of any object whenever its size, shape, and structure are irrelevant in a given context. For example, from far enough away, any finite-size object will look and behave as a point-like object. Point masses and point charges, discussed below, are two common cases.
Point mass distribution - search.r-project.org
Point mass distribution Description. Density, distribution function, quantile function and random generation for point distribution. Usage dpoint(x, location, log = FALSE) rpoint(n, location) ppoint(q, location, lower.tail = TRUE, log.p = FALSE) qpoint(p, location, lower.tail = TRUE, log.p = FALSE) Arguments
Point mass distribution — point • BayesTools - fbartos.github.io
Density, distribution function, quantile function and random generation for point distribution.