Returns the Hamming distance of string1 and string2, i.e. the number of positions at which the corresponding characters are different. Note that the two strings must have the same length.
Decodes a Base64-encoded string back into its original binary form. This function is capable of handling both fully padded and non-padded Base64 encoded strings. Partially padded Base64 strings are not supported and will result in a “UserError” status being returned.
Compute the Beta cdf with given a, b parameters: P(N < value; a, b). The a, b parameters must be positive real numbers and value must be a real value (all of type DOUBLE). The value must lie on the interval [0, 1].
Compute the Binomial cdf with given numberOfTrials and successProbability (for a single trial): P(N < value). The successProbability must be real value in [0, 1], numberOfTrials and value must be positive integers with numberOfTrials greater or equal to value.
Compute the Cauchy cdf with given parameters median and scale (gamma): P(N; median, scale). The scale parameter must be a positive double. The value parameter must be a double on the interval [0, 1].
Compute the Chi-square cdf with given df (degrees of freedom) parameter: P(N < value; df). The df parameter must be a positive real number, and value must be a non-negative real value (both of type DOUBLE).
Compute the F cdf with given df1 (numerator degrees of freedom) and df2 (denominator degrees of freedom) parameters: P(N < value; df1, df2). The numerator and denominator df parameters must be positive real numbers. The value must be a non-negative real number.
Compute the Gamma cdf with given shape and scale parameters: P(N < value; shape, scale). The shape and scale parameters must be positive real numbers. The value must be a non-negative real number.
Compute the inverse of the Beta cdf with given a, b parameters for the cumulative probability (p): P(N < n). The a, b parameters must be positive double values. The probability p must lie on the interval [0, 1].
Compute the inverse of the Binomial cdf with given numberOfTrials and successProbability (of a single trial) the cumulative probability (p): P(N <= n). The successProbability and p must be real values in [0, 1] and the numberOfTrials must be a positive integer.
Compute the inverse of the Cauchy cdf with given parameters median and scale (gamma) for the probability p. The scale parameter must be a positive double. The probability p must be a double on the interval [0, 1].
Compute the inverse of the Chi-square cdf with given df (degrees of freedom) parameter for the cumulative probability (p): P(N < n). The df parameter must be positive real values. The probability p must lie on the interval [0, 1].
Compute the inverse of the Fisher F cdf with a given df1 (numerator degrees of freedom) and df2 (denominator degrees of freedom) parameters for the cumulative probability (p): P(N < n). The numerator and denominator df parameters must be positive real numbers. The probability p must lie on the interval [0, 1].
Compute the inverse of the Gamma cdf with given shape and scale parameters for the cumulative probability (p): P(N < n). The shape and scale parameters must be positive real values. The probability p must lie on the interval [0, 1].
Compute the inverse of the Laplace cdf with given mean and scale parameters for the cumulative probability (p): P(N < n). The mean must be a real value and the scale must be a positive real value (both of type DOUBLE). The probability p must lie on the interval [0, 1].
Compute the inverse of the Normal cdf with given mean and standard deviation (sd) for the cumulative probability (p): P(N < n). The mean must be a real value and the standard deviation must be a real and positive value (both of type DOUBLE). The probability p must lie on the interval (0, 1).
Compute the inverse of the Poisson cdf with given lambda (mean) parameter for the cumulative probability (p). It returns the value of n so that: P(N <= n; lambda) = p. The lambda parameter must be a positive real number (of type DOUBLE). The probability p must lie on the interval [0, 1).
Compute the inverse of the Weibull cdf with given parameters a, b for the probability p. The a, b parameters must be positive double values. The probability p must be a double on the interval [0, 1].
Compute the Laplace cdf with given mean and scale parameters: P(N < value; mean, scale). The mean and value must be real values and the scale parameter must be a positive value (all of type DOUBLE).
Compute 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 standard deviation must be a real and positive value (all of type DOUBLE).
Compute the Poisson cdf with given lambda (mean) parameter: P(N <= value; lambda). The lambda parameter must be a positive real number (of type DOUBLE) and value must be a non-negative integer.