whereas the main purpose of this correspondence is to clarify the concept of a density function for a complex random variable, and to discuss its properties. Two different functions play the role that ...

The trick of the proposed approach is to replace inequalities that appear in the CDF calculation with unit step functions and to use complex integral representation of the the unit step function ...

A discrete random variable is a type of random variable that can take on a countable set of distinct values. Common examples include the number of children in a family, the outcome of rolling a die, ...

This valuable study investigates how stochastic and deterministic factors are integrated during cellular decision-making, particularly in situations where cells differentiate into distinct fates ...

This gives a visual depiction of the distribution of the data, similar to a histogram or probability distribution function ... Cleveland dot plot lists the variable as a continuous one rather ...

Some functionality may not work correctly outside of this environment. Note: Support for these distributions is under development. Some functions may not be fully implemented or may produce unexpected ...

This can used as a reference sheet for Probability in this course! We also have variables for values like \(a\). Note that these variables are also represented by lower case letters and only represent ...

Visually, the larger the variance, the "fatter" a probability distribution will be. In finance, if something like an investment has a greater variance, it may be interpreted as more risky or volatile.

The Browser Company shifts focus from Arc to Dia, an AI-powered browser, placing Arc in maintenance as it explores open sourcing or selling it. Dark LLMs like WormGPT bypass safety limits to aid ...

Rather than track every swirl, some researchers treat the entire process statistically by defining a probability distribution function for the fluid’s fluctuations. This distribution-based view ...

The central theme of this approach is to properly imbed the random variables of interest into the framework of a finite Markov chain, and the resulting representations of the underlying distributions ...