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  2. Moving average - Wikipedia

    en.wikipedia.org/wiki/Moving_average

    However, it is possible to simply update cumulative average as a new value, + becomes available, using the formula + = + + +. Thus the current cumulative average for a new datum is equal to the previous cumulative average, times n , plus the latest datum, all divided by the number of points received so far, n +1.

  3. Cumulant - Wikipedia

    en.wikipedia.org/wiki/Cumulant

    The cumulative property follows quickly by considering the cumulant-generating function: + + = ⁡ ⁡ [(+ +)] = ⁡ (⁡ [] ⁡ []) = ⁡ ⁡ [] + + ⁡ ⁡ [] = + + (), so that each cumulant of a sum of independent random variables is the sum of the corresponding cumulants of the addends. That is, when the addends are statistically ...

  4. Cumulative distribution function - Wikipedia

    en.wikipedia.org/wiki/Cumulative_distribution...

    Cumulative distribution function for the exponential distribution Cumulative distribution function for the normal distribution. In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable, or just distribution function of , evaluated at , is the probability that will take a value less than or equal to .

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The probability density, cumulative distribution, and inverse cumulative distribution of any function of one or more independent or correlated normal variables can be computed with the numerical method of ray-tracing [41] (Matlab code). In the following sections we look at some special cases.

  6. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    where is the normal cumulative distribution function. The derivation of the formula is provided in the Talk page. The partial expectation formula has applications in insurance and economics, it is used in solving the partial differential equation leading to the Black–Scholes formula.

  7. Triangular distribution - Wikipedia

    en.wikipedia.org/wiki/Triangular_distribution

    This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]

  8. Failure rate - Wikipedia

    en.wikipedia.org/wiki/Failure_rate

    A concept closely-related but different [2] to instantaneous failure rate () is the hazard rate (or hazard function), (). In the many-system case, this is defined as the proportional failure rate of the systems still functioning at time t {\displaystyle t} (as opposed to f ( t ) {\displaystyle f(t)} , which is the expressed as a proportion of ...

  9. Rate of return - Wikipedia

    en.wikipedia.org/wiki/Rate_of_return

    The geometric average return is equivalent to the cumulative return over the whole n periods, converted into a rate of return per period. Where the individual sub-periods are each equal (say, 1 year), and there is reinvestment of returns, the annualized cumulative return is the geometric average rate of return.