Noun:

সম্ভাব্যতার সূত্রাবলি দ্বারা প্রক্রিয়া,

stochastic process's Usage Examples:

integer-valued stochastic process.

If the state space is the real line, then the stochastic process is referred to as a real-valued stochastic process or a process.

strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional joint probability distribution does not change.

In probability theory, a continuous stochastic process is a type of stochastic process that may be said to be "continuous" as a function of its "time".

In the mathematics of probability, a stochastic process is a random function.

The amount of time required for a stochastic process, starting from some initial state, to encounter a threshold for the.

statistics, a continuous-time stochastic process, or a continuous-space-time stochastic process is a stochastic process for which the index variable takes.

the term Markov property refers to the memoryless property of a stochastic process.

In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that.

Furthermore, in probability theory, the formal concept of a stochastic process is also referred to as a random process.

"consistent" collection of finite-dimensional distributions will define a stochastic process.

which one or more of the terms is a stochastic process, resulting in a solution which is also a stochastic process.

Empirical process, a stochastic process that describes the proportion of objects in a system in a given state Lévy process, a stochastic process with independent.

stochastic process whose sample paths are almost surely continuous functions.

stochastic process with some restriction on its index set.

That is, by modern definitions, a random field is a generalization of a stochastic process.

the mathematical theory of probability, a predictable process is a stochastic process whose value is knowable at a prior time.

Kolmogorov continuity theorem is a theorem that guarantees that a stochastic process that satisfies certain constraints on the moments of its increments.

In mathematics, a Feller-continuous process is a continuous-time stochastic process for which the expected value of suitable statistics of the process.

, a stochastic process) for which, at a particular time, the conditional expectation of the.

The sequence in which each of the phases occur may itself be a stochastic process.

Synonyms:

model; Markov process; stationary stochastic process; Markoff process; random walk; theoretical account; framework;

Antonyms:

follower; unworthy;