You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: skipped_correlation.m
    path of file: ./repos/bspm/thirdparty/corr_toolbox_v2
    
    the code of the file until where you have to start completion: function [r,t,h,outid,hboot,CI]=skipped_correlation(x,y,fig_flag)

% performs a robust correlation using pearson/spearman correlation on
% data cleaned up for bivariate outliers - that is after finding the
% central point in the distribution using the mid covariance determinant,
% orthogonal distances are computed to this point, and any data outside the
% bound defined by the idealf estimator of the interquartile range is removed.
% 
% FORMAT:

    
function [r,t,h,outid,hboot,CI]=skipped_correlation(x,y,fig_flag)

% performs a robust correlation using pearson/spearman correlation on
% data cleaned up for bivariate outliers - that is after finding the
% central point in the distribution using the mid covariance determinant,
% orthogonal distances are computed to this point, and any data outside the
% bound defined by the idealf estimator of the interquartile range is removed.
% 
% FORMAT:
%          [r,t,h] = skipped_correlation(X,Y);
%          [r,t,h] = skipped_correlation(X,Y,fig_flag);
%          [r,t,h,outid,hboot,CI] = skipped_correlation(X,Y,fig_flag);
%
% INPUTS:  X and Y are 2 vectors or matrices, in the latter case,
%          correlations are computed column-wise 
%          fig_flag (1/0) indicates to plot the data or not
%
% OUTPUTS:
%          r is the pearson/spearman correlation 
%          t is the T value associated to the skipped correlation
%          h is the hypothesis of no association at alpha = 5% 
%          outid is the index of bivariate outliers
% 
%          optional:
%
%          hboot 1/0 declares the test significant based on CI (h depend