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  2. Logit-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Logit-normal_distribution

    In probability theory, a logit-normal distribution is a probability distribution of a random variable whose logit has a normal distribution.If Y is a random variable with a normal distribution, and t is the standard logistic function, then X = t(Y) has a logit-normal distribution; likewise, if X is logit-normally distributed, then Y = logit(X)= log (X/(1-X)) is normally distributed.

  3. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    In regression analysis, logistic regression [1] ... Comparison of logistic function with a scaled inverse probit function (i.e. the CDF of the normal distribution), ...

  4. Logistic distribution - Wikipedia

    en.wikipedia.org/wiki/Logistic_distribution

    In probability theory and statistics, the logistic distribution is a continuous probability distribution. Its cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks. It resembles the normal distribution in shape but has heavier tails (higher kurtosis).

  5. Logit - Wikipedia

    en.wikipedia.org/wiki/Logit

    The logit and probit are both sigmoid functions with a domain between 0 and 1, which makes them both quantile functions – i.e., inverses of the cumulative distribution function (CDF) of a probability distribution. In fact, the logit is the quantile function of the logistic distribution, while the probit is the quantile function of the normal ...

  6. Generalized linear model - Wikipedia

    en.wikipedia.org/wiki/Generalized_linear_model

    In linear regression, the use of the least-squares estimator is justified by the Gauss–Markov theorem, which does not assume that the distribution is normal. From the perspective of generalized linear models, however, it is useful to suppose that the distribution function is the normal distribution with constant variance and the link function ...

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...

  8. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    When the larger values tend to be farther away from the mean than the smaller values, one has a skew distribution to the right (i.e. there is positive skewness), one may for example select the log-normal distribution (i.e. the log values of the data are normally distributed), the log-logistic distribution (i.e. the log values of the data follow ...

  9. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    In this context, the log-normal distribution has shown a good performance in two main use cases: (1) predicting the proportion of time traffic will exceed a given level (for service level agreement or link capacity estimation) i.e. link dimensioning based on bandwidth provisioning and (2) predicting 95th percentile pricing. [87]