Add to ORKGRandom variable, conditional distribution, bivariate normal distributionIf X is a normal random variable and the conditional distribution of Y given X=x is (1) normal, (2) has a mean that is a linear function of x, and (3) has a variance that is constant (does not depend on x), then the pair (X,Y) follows a bivariate normal distribution. The left image is a graph of the bivariate density function and the right image shows the conditional distribution of Y when X takes the value of the x sliderComponente Curricular::Educação Superior::Ciências Exatas e da Terra::Matemátic
AbstractIt is shown that the conditional probability density function of Y1 given (1n) Σi=1n Yi=1Yit...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...
Distribution, density function, standard deviations, normal distributionThe bivariate normal distrib...
Distribution, density function, standard deviations, normal distributionThe bivariate normal distrib...
AbstractIt is well known that full knowledge of all conditional distributions will typically serve t...
Conditional specification, conditional distribution, regression function, bivariate probability dist...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
Let $X$ and $Y$ be two random vectors with values in $\bbfR\sp k$ and $\bbfR\sp \ell$, respectively....
If X is a k-dimensional random vector, we denote by X(i) the vector X with coordinate i deleted and ...
In this paper we give a characterization of the multivariate normal distribution through the conditi...
In this paper the relationship between joint density and conditional densities is studied. An explic...
Random variables are rarely independent in practice and so many multivariate distributions have been...
The thesis deals with three selected constructions of bivariate distributions. The first approach is...
AbstractIt is shown that the conditional probability density function of Y1 given (1n) Σi=1n Yi=1Yit...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...
Distribution, density function, standard deviations, normal distributionThe bivariate normal distrib...
Distribution, density function, standard deviations, normal distributionThe bivariate normal distrib...
AbstractIt is well known that full knowledge of all conditional distributions will typically serve t...
Conditional specification, conditional distribution, regression function, bivariate probability dist...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
Let $X$ and $Y$ be two random vectors with values in $\bbfR\sp k$ and $\bbfR\sp \ell$, respectively....
If X is a k-dimensional random vector, we denote by X(i) the vector X with coordinate i deleted and ...
In this paper we give a characterization of the multivariate normal distribution through the conditi...
In this paper the relationship between joint density and conditional densities is studied. An explic...
Random variables are rarely independent in practice and so many multivariate distributions have been...
The thesis deals with three selected constructions of bivariate distributions. The first approach is...
AbstractIt is shown that the conditional probability density function of Y1 given (1n) Σi=1n Yi=1Yit...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...
The probability mass function of a pair of discrete random variables (X,Y) is the function f(x,y)=P(...