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  2. Continuity in probability - Wikipedia

    en.wikipedia.org/wiki/Continuity_in_probability

    Feller processes are continuous in probability at =. Continuity in probability is a sometimes used as one of the defining property for Lévy process . [ 1 ] Any process that is continuous in probability and has independent increments has a version that is càdlàg . [ 2 ]

  3. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    An absolutely continuous probability distribution is a probability distribution on the real numbers with uncountably many possible values, such as a whole interval in the real line, and where the probability of any event can be expressed as an integral. [19]

  4. Continuous stochastic process - Wikipedia

    en.wikipedia.org/wiki/Continuous_stochastic_process

    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" or index parameter. Continuity is a nice property for (the sample paths of) a process to have, since it implies that they are well-behaved in some sense, and, therefore, much easier to analyze.

  5. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the ...

  6. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈ w aɪ b ʊ l / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.

  7. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/wiki/Continuous_uniform...

    Any probability density function integrates to , so the probability density function of the continuous uniform distribution is graphically portrayed as a rectangle where ⁠ ⁠ is the base length and ⁠ ⁠ is the height. As the base length increases, the height (the density at any particular value within the distribution boundaries) decreases.

  8. Conditional probability distribution - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability...

    If the conditional distribution of given is a continuous distribution, then its probability density function is known as the conditional density function. [1] The properties of a conditional distribution, such as the moments , are often referred to by corresponding names such as the conditional mean and conditional variance .

  9. Law of total probability - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_probability

    The term law of total probability is sometimes taken to mean the law of alternatives, which is a special case of the law of total probability applying to discrete random variables. [ citation needed ] One author uses the terminology of the "Rule of Average Conditional Probabilities", [ 4 ] while another refers to it as the "continuous law of ...

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