For vectors, Y = RUNMEAN(X,M) computes a running mean (also known as moving average) on the elements of the vector X. It uses a window of 2*M+1 datapoints. M an positive integer defining (half) the size of the window. In pseudo code:
Y(i) = sum(X(j)) / (2*M+1), for j = (i-M):(i+M), and i=1:length(X)

For matrices, Y = RUNMEAN(X,M) or RUNMEAN(X,M,[]) operates on the first non-singleton dimension of X. RUNMEAN(X,M,DIM) computes the running mean along the dimension DIM.

If the total window size (2*M+1) is larger than the size in dimension DIM, the overall average along dimension DIM is computed.

As always with filtering, the values of Y can be inaccurate at the edges. RUNMEAN(..., MODESTR) determines how the edges are treated. MODESTR can be one of the following strings:
'edge' : X is padded with first and last values along dimension DIM (default)
'zero' : X is padded with zeros
'mean' : X is padded with the mean along dimension DIM

X should not contains NaNs, yielding an all NaN result. NaNs can be replaced by using, e.g., "inpaint_nans" created by John D'Errico.

This is an incredibly fast implementation of a running mean, since execution time does not depend on the size of the window.

This is version 3.0 (sep 19, 2006). The previous posted code of version 1.3 is attached at the end.