empirical_cdf

Empirical cumulative distribution function

Syntax

   P = empirical_cdf(x,X,ptails,ksmooth)

Arguments

See also Common variable names and data structures.

input

   x          vector of statistic values
   X          vector of sample statistics
   ptails     Pareto tails lower and upper probabilities (default: no Pareto tails)
   ksmooth    use kernel smoothing to estimate cdf (default: no smoothing)

output

   P          cumulative distribution probabilities evaluated at x

Description

Returns the empirical cumulative distribution function estimated from sample statistics in vector X, evaluated at values in vector x. For p-values, X should be drawn from the appropriate null distribution (see empirical_pval).

Uses the Matlab Statistics Toolbox paretotails class to estimate the cdf. Pareto tails for the cumulative distribution may be specified by the 2-vector ptails, with lower and upper cumulative probabilities in ptails(1) and ptails(2) respectively [where |0 ptails(1) < ptails(2) <= 1|]. If the ksmooth flag is set, then kernel smoothing is used to estimate the cdf, otherwise simple midpoint interpolation; see <matlab:doc('paretotails') paretotails for details.

See also

empirical_cdfi | empirical_pval | empirical_confint | empirical_cval | mvgc_demo_permtest | paretotails