Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...

Artificial intelligence (AI) applied to abdominal imaging can help predict adults at higher risk of falling as early as ...

This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for ...

In this paper, we consider the function f p ( t )= 2p X 2 ( 2p t+p;p ) , where χ²(x; n) defined by X 2 ( x;p )= 2 −p/2 Γ( p/2 ) e −x/2 x p/2−1 , is the density function of a χ²-distribution with n ...

Abstract: When the estimated parameter values are close to the true values, the probability density function of output with the estimated will be close to the probability density function with the ...

Abstract: Support vector machine(SVM) is a new approach for probability density estimation problems. But there are some shortcomings in the SVM based method, for example, the method can only optimize ...

The Principal Component Analysis (PCA) is a procedure extensively employed in data science with diverse purposes. It has found widespread use in making sense of data collected from Molecular Dynamics ...

What Is A Probability Density Function? A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable ...

Cumulative probability is an essential concept in the world of statistics and probability theory. It refers to the likelihood that a random variable will take a value equal to or less than a specific ...