Exemplos de uso de Textstyle em Inglês e suas traduções para o Português
{-}
-
Colloquial
-
Official
-
Medicine
-
Financial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
-
Official/political
For virtual images,M{\textstyle M} is positive and the image is upright.
In general, if X is a class all of whose elements are transitive sets,then X∪⋃ X{\textstyle X\cup\bigcup X} is transitive.
Note that for real images,M{\textstyle M} is negative and the image is inverted.
If f{\textstyle f} is zero the equation is called homogeneous, otherwise it is called inhomogeneous.
In other words,the parameter λ{\displaystyle\textstyle\lambda} of the Poisson process coincides with the density of points.
The Householder transformation is a reflection about a hyperplane with unit normal vector v{\textstyle v}, as stated earlier.
It follows that λ{\displaystyle\textstyle\lambda} is the expected number of arrivals that occur per unit of time.
The theorem involves some Poisson point process with mean measure Λ{\displaystyle\textstyle\Lambda} on some underlying space.
For λ 1{\displaystyle\textstyle\lambda =1}, the corresponding process is sometimes referred to as the standard Poisson(point) process.
A counting process represents the total number of occurrences or events that have happened up to andincluding time t{\displaystyle\textstyle t.
For the Poisson process,the independent p( x){\displaystyle\textstyle p(x)}-thinning operations results in another Poisson point process.
For the inhomogeneous,a couple of different methods can be used depending on the nature of the intensity function λ( x){\displaystyle\textstyle\lambda x.
The reflection hyperplane can be defined by a unit vector v{\textstyle v}(a vector with length 1{\textstyle 1}) which is orthogonal to the hyperplane.
For the homogeneous case in one dimension, all points are uniformly and independently placed in the window orinterval W{\displaystyle\textstyle W.
This set A{\displaystyle\textstyle A} is formed by a finite number of unions, whereas a Borel set is formed by a countable number of set operations.
For higher dimensions in a Cartesian coordinate system, each coordinate is uniformly andindependently placed in the window W{\displaystyle\textstyle W.
If the original process N{\displaystyle\textstyle{N}} is a Poisson point process, then the resulting process N c{\displaystyle\textstyle{N}_{c}} is called a Poisson cluster point process.
Poisson derived the Poisson distribution, published in 1841,by examining the binomial distribution in the limit of p{\displaystyle\textstyle p}(to zero) and n{\displaystyle\textstyle n} to infinity.
If N{\displaystyle\textstyle{N}} is a Poisson point process, then the new process N′{\displaystyle\textstyle{N}'} is also a Poisson point process with the intensity measure Λ′{\displaystyle\textstyle\Lambda.
The Poisson point process can be further generalized to what is sometimes known as the general Poisson point process or general Poisson process by using a Radon measure Λ{\displaystyle\textstyle\Lambda}, which is locally-finite measure.
If the homogeneous Poisson process is considered just on the half-line{\displaystyle\textstyle a, b} where a≤ b{\displaystyle\textstyle a\leq b}, then its location will be a uniform random variable defined on that interval.
For example, given a homogeneous Poisson point process on the real line,the probability of finding a single point of the process in a small interval of width δ{\displaystyle\textstyle\delta} is approximately λ δ x{\displaystyle\textstyle\lambda\delta x.
The number of points N{\displaystyle\textstyle N} in the window, denoted here by W{\displaystyle\textstyle W}, needs to be simulated, which is done by using a(pseudo)-random number generating function capable of simulating Poisson random variables.
The distance between two consecutive points of a point process on the real line will be an exponential random variable with parameter λ{\displaystyle\textstyle\lambda} or equivalently, mean 1/ λ{\displaystyle\textstyle 1/\lambda.
One version of the displacement theorem involves a Poisson point process N{\displaystyle\textstyle{N}} on R d{\displaystyle\textstyle{\textbf{R}}^{d}} with intensity function λ( x){\displaystyle\textstyle\lambda x.
Furthermore, it has a third feature related to just the homogeneous Poisson point process: the Poisson distribution of the number of arrivals in each interval a+ t,b+ t{\displaystyle\textstyle a+t, b+t} only depends on the interval's length b- a{\displaystyle\textstyle b-a.