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2. Half-logistic distribution - Wikipedia

   en.wikipedia.org/wiki/Half-logistic_distribution

   The cumulative distribution function (cdf) of the half-logistic distribution is intimately related to the cdf of the logistic distribution. Formally, if F(k) is the cdf for the logistic distribution, then G(k) = 2F(k) − 1 is the cdf of a half-logistic distribution. Specifically,

3. 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 .

4. Generalized beta distribution - Wikipedia

   en.wikipedia.org/wiki/Generalized_Beta_distribution

   The beta family includes the beta of the first and second kind [7] (B1 and B2, where the B2 is also referred to as the Beta prime), which correspond to c = 0 and c = 1, respectively. Setting c = 0 {\displaystyle c=0} , b = 1 {\displaystyle b=1} yields the standard two-parameter beta distribution .

5. Normal distribution - Wikipedia

   en.wikipedia.org/wiki/Normal_distribution

   In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable.The general form of its probability density function is [2] [3] = ().

6. Beta distribution - Wikipedia

   en.wikipedia.org/wiki/Beta_distribution

   In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.

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. 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.

9. Weibull modulus - Wikipedia

   en.wikipedia.org/wiki/Weibull_modulus

   CDF of Weibull distribution for the example of predicting failure in materials, σ 0 = 50 MPa. The Weibull distribution, represented as a cumulative distribution function (CDF), is defined by: = ⁡ (()) in which m is the Weibull modulus.