Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution by numerically integrating the ChiSquare probability density function (pdf).
Compute the Cumulative Distribution Function (CDF) for the ChiSquare distribution by numerically integrating the ChiSquare probability density function (pdf). See Variate.scala.
the x coordinate
the degrees of freedom
Compute the p-th quantile for "ChiSquare distribution" function.
Compute the p-th quantile for "ChiSquare distribution" function.
the p-th quantile, e.g., .95 (95%)
the degrees of freedom
Compute the p-th quantile for "ChiSquare distribution" function using bisection search of the CDF.
Compute the p-th quantile for "ChiSquare distribution" function using bisection search of the CDF.
the p-th quantile, e.g., .95 (95%)
the degrees of freedom
Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.
Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.
the p-th quantile, e.g., .95 (95%)
the pair of degrees of freedom (df1, df2)
Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.
Compute the Cumulative Distribution Function (CDF) for the Fisher (F) distribution using beta functions.
the p-th quantile, e.g., .95 (95%)
the degrees of freedom 1
the degrees of freedom 2
Compute the p-th quantile for "Fisher (F) distribution" function.
Compute the p-th quantile for "Fisher (F) distribution" function.
the p-th quantile, e.g., .95 (95%)
the pair of degrees of freedom (df1 and df2)
Compute the p-th quantile for "Fisher (F) distribution" function using bisection search of the CDF.
Compute the p-th quantile for "Fisher (F) distribution" function using bisection search of the CDF.
the p-th quantile, e.g., .95 (95%)
the degrees of freedom
Show the flaw by printing the error message.
Show the flaw by printing the error message.
the method where the error occurred
the error message
Compute the p-th quantile for the "standard normal distribution" function.
Compute the p-th quantile for the "standard normal distribution" function. This function returns an approximation of the "inverse" cumulative standard normal distribution function. I.e., given p, it returns an approximation to the x satisfying p = P{Z <= x} where Z is a random variable from the standard normal distribution. The algorithm uses a minimax approximation by rational functions and the result has a relative error whose absolute value is less than 1.15e-9. Author: Peter J. Acklam (Adapted to Scala by John Miller) (Javascript version by Alankar Misra @ Digital Sutras (alankar@digitalsutras.com)) Time-stamp: 2003-05-05 05:15:14 E-mail: pjacklam@online.no WWW URL: http://home.online.no/~pjacklam
the p-th quantile, e.g., .95 (95%)
the degrees of freedom (not used for Normal)
Compute the p-th quantile for "Student's t distribution" function.
Compute the p-th quantile for "Student's t distribution" function.
the p-th quantile, e.g., 95 (95%)
the degrees of freedom
Compute the p-th quantile for "Student's t distribution" function.
Compute the p-th quantile for "Student's t distribution" function. This function returns an approximation of the "inverse" cumulative Student's t distribution function. I.e., given p, it returns an approximation to the x satisfying p = P{T <= x} where T is a random variable from Student's t distribution. From K. Pawlikowski (www.cosc.canterbury.ac.nz). This function computes the upper p-th quantile of the t distribution (the value of t for which the area under the curve from t to +infinity is equal to p). It is a transliteration of the 'STUDTP' function given in Appendix C of "Principles of Discrete Event Simulation", G. S. Fishman, Wiley, 1978.
the p-th quantile, e.g., 95 (95%)
the degrees of freedom
The
Quantileobject contains methods for computing 'Finv', the inverse Cumulative Distribution Functions (iCDF's) for popular sampling distributions: StandardNormal, StudentT, ChiSquare and Fisher. For a given CDF 'F' and quantile 'p', compute 'x' such that the 'F(x) = p'.