Reconstruct a Distribution from a Collection of Quantiles

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Documentation for package ‘distfromq’ version 1.0.4

• DESCRIPTION file.
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duplicated_tol	Identify duplicated values in a sorted numeric vector, where comparison is up to a specified numeric tolerance. If there is a run of values where each consecutive pair is closer together than the tolerance, all are labeled as duplicates even if not all values in the run are within the tolerance.
get_dup_run_inds	Get indices of starts and ends of runs of duplicate values
make_d_fn	Creates a function that evaluates the probability density function of an approximation to a distribution obtained by interpolating and extrapolating from a set of quantiles of the distribution.
make_p_fn	Creates a function that evaluates the cumulative distribution function of an approximation to a distribution obtained by interpolating and extrapolating from a set of quantiles of the distribution.
make_q_fn	Creates a function that evaluates the quantile function of an approximation to a distribution obtained by interpolating and extrapolating from a set of quantiles of the distribution.
make_r_fn	Creates a function that generates random deviates from an approximation to a distribution obtained by interpolating and extrapolating from a set of quantiles of the distribution.
mono_Hermite_spline	Create a polySpline object representing a monotonic Hermite spline interpolating a given set of points.
spline_cdf	Approximate density function, CDF, or quantile function on the interior of provided quantiles by representing the distribution as a sum of a discrete part at any duplicated 'qs' and a continuous part for which the CDF is estimated using a monotonic Hermite spline. See details for more.
split_disc_cont_ps_qs	Split ps and qs into those corresponding to discrete and continuous parts of a distribution.
step_interp_factory	A factory that returns a function that performs linear interpolation, allowing for "steps" or discontinuities.
unique_tol	Get unique values in a sorted numeric vector, where comparison is up to a specified numeric tolerance. If there is a run of values where each consecutive pair is closer together than the tolerance, all are labeled as corresponding to a single unique value even if not all values in the run are within the tolerance.