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  2. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln( X ) has a normal distribution.

  3. Negative log predictive density - Wikipedia

    en.wikipedia.org/wiki/Negative_log_predictive...

    Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; ... In statistics, the negative log predictive density (NLPD) is a ...

  4. Logarithmically concave function - Wikipedia

    en.wikipedia.org/wiki/Logarithmically_concave...

    The following are among the properties of log-concave distributions: If a density is log-concave, so is its cumulative distribution function (CDF). If a multivariate density is log-concave, so is the marginal density over any subset of variables. The sum of two independent log-concave random variables is log-concave. This follows from the fact ...

  5. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    In probability theory and statistics, Student's t distribution (or simply the t distribution) is a continuous probability distribution that generalizes the standard normal distribution.

  6. Empirical distribution function - Wikipedia

    en.wikipedia.org/wiki/Empirical_distribution...

    In MATLAB we can use Empirical cumulative distribution function (cdf) plot; jmp from SAS, the CDF plot creates a plot of the empirical cumulative distribution function. Minitab, create an Empirical CDF; Mathwave, we can fit probability distribution to our data; Dataplot, we can plot Empirical CDF plot; Scipy, we can use scipy.stats.ecdf

  7. Log-t distribution - Wikipedia

    en.wikipedia.org/wiki/Log-t_distribution

    The log-t distribution has the probability density function: (, ^, ^) = (+) ^ (+ (⁡ ^ ^)) +,where ^ is the location parameter of the underlying (non-standardized) Student's t-distribution, ^ is the scale parameter of the underlying (non-standardized) Student's t-distribution, and is the number of degrees of freedom of the underlying Student's t-distribution. [1]

  8. Logarithmic decrement - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_decrement

    The logarithmic decrement can be obtained e.g. as ln(x 1 /x 3).Logarithmic decrement, , is used to find the damping ratio of an underdamped system in the time domain.. The method of logarithmic decrement becomes less and less precise as the damping ratio increases past about 0.5; it does not apply at all for a damping ratio greater than 1.0 because the system is overdamped.

  9. Log-distance path loss model - Wikipedia

    en.wikipedia.org/wiki/Log-distance_path_loss_model

    The log-distance path loss model is a radio propagation model that predicts the path loss a signal encounters inside a building or densely populated areas over long distance. While the log-distance model is suitable for longer distances, the short-distance path loss model is often used for indoor environments or very short outdoor distances.