Inverse (integrated) gradient by John D'Errico

Vectorized & fully sparse 1-d, 2-d, & 3-d integrated gradients (integration, simpsons rule, gradient)

consolidator(x,y,aggregation_mode,tol)

intgrad1(fx,dx,f1,method)

intgrad2(fx,fy,dx,dy,f11)

Cummulative (dim 2) products across all permutations of distinct column-indices by Hin Kwan Wong

Sum column element products for all permutations of distinct column indices + user restrictions (multinomial, polynomial, expansion)

cumprodapdci(dataArray,varargin)

nancumsum by Brett Shoelson

Compute the cumulative sum of matrices, specifying the treatment of NaNs. (nan, cumulative, sum)

B=nancumsum(A,dim,nmode)

nancumprod by Brett Shoelson

Compute the cumulative product of matrices, specifying the treatment of NaNs. (nan, cumulative, prod)

B=nancumprod(A,dim,nmode)

cumulativ statistic by Mauro

cumstat calculate the mean and std of an array from 1 to n (cumulative, cumulativ, statistic)

cumstat(x,dim)

CUMSIM: "CUMulative SIMpson" integral by Vassili Pastushenko

Integral(y(x),x(1),x(end)) by Simpson. Nonequidistantlysampled data regularuzed by PARFIL (integration, cumulative, nonequidistant)

CS=cumspline(x,y)

ER=compcum

Y=cumsim(varargin)

Bivariate Cumulative Normal Probability by S B

This function gives bivariate cumulative normal probability and also includes normal probability. (bivariate, statistics, probability)

bivnormcdf(a,b,rho)

normcdfM(x)

Kolmogorov Distribution Functions by Sergii Iglin

kolmcdf, kolmpdf, kolminv (statistics, probability, kolmogorov)

kolmcdf(x)

kolminv(p)

kolmpdf(x)

Progressive mean and standard deviation. by Gabriele

Progressive mean and standard deviation. (deviation, standard, mean)

[m_t,s_t]=f_cummeanstd(y);

r2cum by Christopher Brown

Returns a vector containing cumulative r-squared values. (probability, r, correlation)

r2cum(x,y)