Îõ³h$,Ö  Safe-InferredV Auxiliary functions(c) Dominik Schrempf, 2021GPL-3.0-or-laterdominik.schrempf@gmail.comunstableportableNone?ˆpava&Calculate the slope between to points.pava(Check if vector is ordered strictly (<).pava,Fill in missing values of an indexed vector. Ú smooth [-2, 2, 4, 5] [0.0, 4.0, 10.0, 88.0] = [0.0, 1.0, 2.0, 3.0, 4.0, 7.0, 10.0, 88.0] pavaSee .ÝAssume that: - the lengths of the provided vectors are equal; - the predictors are ordered.pavaReverse lists in a three-tuple.Compute least concave majorants(c) Dominik Schrempf, 2021GPL-3.0-or-laterdominik.schrempf@gmail.comunstableportableNone?­pavaºGreatest convex minorant. Uses the Pool Adjacent Violators Algorithm (PAVA). It is required that the predictors are ordered with no ties, and that the lengths of the vectors are equal.Usage: 6 lcm predictors responses = (indices, values, slopes) pavaSee .ÝAssume that: - the lengths of the provided vectors are equal; - the predictors are ordered.!Compute greatest convex minorants(c) Dominik Schrempf, 2021GPL-3.0-or-laterdominik.schrempf@gmail.comunstableportableNone?ÎpavaºGreatest convex minorant. Uses the Pool Adjacent Violators Algorithm (PAVA). It is required that the predictors are ordered with no ties, and that the lengths of the vectors are equal.Usage: 6 gcm predictors responses = (indices, values, slopes) pavaSee .ÝAssume that: - the lengths of the provided vectors are equal; - the predictors are ordered.     #pava-0.1.1.2-AhzWQzhwukHLtw3KKR3wrcStatistics.Pava.CommonStatistics.LcmStatistics.Gcm Paths_pavaslopestrictlyOrderedsmooth unsafeSmoothreverse3lcm unsafeLcmgcm unsafeGcmversion getBinDir getLibDir getDynLibDir getDataDir getLibexecDir getSysconfDirgetDataFileName