Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Commonly used distributions Normal distribution ( ) Formula: ( ) √ Domain: Parameters: Mean standard deviation Uniform distribution (real number form) ( ) Formula: { Domain: Parameters: Low X, High X Uniform distribution (integer number form) ( ) Formula: { Domain: Parameters: Triangular distribution Formula: ( ) { ( ) ( ) ( Domain: Parameters: Low X, Mode (likeliest), High X ) Fractile distributions (10/50/90 et al) Formula: Equal probability for Low X and High X (e.g., .30 or .25, remainder for Median, 0 for other values. Domain: Low X, Median X, High X Parameters: Low X, Median X, High X More continuous distributions Beta distribution (integer form) Formula: ( ( ) ( ) )( ( ) ) Domain: Parameters: Details: Beta distribution (real number form) Formula: ( ( ) )( )( ) ( ) ( ) ( ) Domain: Parameters: Details: ( ) The parameters a and b can be approximated from a mean μ and standard deviation σ: ( ( ( ) )( ( ) ) ) Dirichlet distribution (multivariate, normalized beta) Formula: where ∑ where ∑ Domain: Parameters: Details: See Chapter 22. Chi distribution Formula: ( ) ( ) ( ( ) Domain: Parameters: Chi-Squared distribution Formula: Domain: Parameters: ( ) ( ( ) ) ( ) ) Erlang distribution Formula: ( ) ( ) ( ) Domain: Parameters: Exponential distribution Formula: ( ) Domain: Parameters: Gamma distribution Formula: ( ) ( ) ( ) Domain: Parameters: Details: The parameters and can be approximated from a mean μ and standard deviation σ: Hyper-exponential distribution Formula: ( ) ( Domain: Parameters: Laplace distribution Formula: | ( ) | Domain: Parameters: Logistic distribution Formula: Domain: Parameters: ( ) ( ( ) ( )) ) ( ) Lognormal distribution Formula: ( ( ) ( ( ) ) ) √ Domain: Parameters: Details: The parameters and are the mean and standard deviation respectively, from the distribution of the ln(x), and can be approximated: ( √ ) ( ) Maxwell distribution Formula: ( ) √ Domain: Parameters: Rayleigh distribution Formula: Domain: Parameters: ( ) ( ) Weibull distribution Formula: ( ) Domain: Parameters: More discrete distributions Binomial distribution Formula: ( ) ( ) ( ) Domain: Parameters: Poisson distribution Formula: Domain: Parameters: ( )