weibull_cdf ( a, b, value ) → double #Ĭompute the Weibull cdf with given parameters a, b: P(N <= value). The lambda parameter must be a positive real number (of type DOUBLE) and value must be a non-negative integer. poisson_cdf ( lambda, value ) → double #Ĭompute the Poisson cdf with given lambda (mean) parameter: P(N <= value lambda). The mean and value must be real values and the standard deviation must be a realĪnd positive value (all of type DOUBLE). normal_cdf ( mean, sd, value ) → double #Ĭompute the Normal cdf with given mean and standard deviation (sd): P(N < value mean, sd). The mean and value must be real values and the scale parameter must be a positive value (all of type DOUBLE). laplace_cdf ( mean, scale, value ) → double #Ĭompute the Laplace cdf with given mean and scale parameters: P(N < value mean, scale). The value must be a non-negative real number. The shape and scale parameters must be positive real numbers. gamma_cdf ( shape, scale, value ) → double #Ĭompute the Gamma cdf with given shape and scale parameters: P(N < value shape, scale). The numerator and denominator df parameters must be positive real numbers. f_cdf ( df1, df2, value ) → double #Ĭompute the F cdf with given df1 (numerator degrees of freedom) and df2 (denominator degrees of freedom) parameters: P(N < value df1, df2). The df parameter must be a positive real number, and value must be a non-negative real value (both of type DOUBLE). chi_squared_cdf ( df, value ) → double #Ĭompute the Chi-square cdf with given df (degrees of freedom) parameter: P(N < value df). The value parameter must be a double on the interval. The scale parameter must be a positive double. cauchy_cdf ( median, scale, value ) → double #Ĭompute the Cauchy cdf with given parameters median and scale (gamma): P(N median, scale). Positive integers with numberOfTrials greater or equal to value. The successProbability must be real value in, numberOfTrials and value must be binomial_cdf ( numberOfTrials, successProbability, value ) → double #Ĭompute the Binomial cdf with given numberOfTrials and successProbability (for a single trial): P(N < value). The a, b parameters must be positive real numbers and value must be a real value (all of type DOUBLE). Probability Functions: cdf # beta_cdf ( a, b, value ) → double #Ĭompute the Beta cdf with given a, b parameters: P(N < value a, b). The bins parameter must be an array of doubles and isĪssumed to be in sorted ascending order. Returns the bin number of x according to the bins specified by theĪrray bins. Specified bound1 and bound2 bounds and n number of buckets. Returns the bin number of x in an equi-width histogram with the Truncate(REAL '12.333', 1) -> result is 12.3 width_bucket ( x, bound1, bound2, n ) → bigint # Returns a pseudo-random value in the range 0.0 result is 10.0 radians ( x ) → double #Ĭonverts angle x in degrees to radians. Returns the modulus (remainder) of n divided by m. Returns the value of string interpreted as a base- radix number. Returns x rounded down to the nearest integer. Returns Euler’s number raised to the power of x. SELECT cosine_similarity ( MAP ( ARRAY, ARRAY ), MAP ( ARRAY, ARRAY )) - 1.0 degrees ( x ) → double #Ĭonverts angle x in radians to degrees. Mathematical Functions and Operators Mathematical Functions and Operators Contents.
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