correlation

I have a list of points I want to check for autocorrelation using Moran's I and by dividing area of interest by 4 x 4 quadrats. Now every example I found on Google (e. g. http://www.ats.ucla.edu/stat/r/faq/morans_i.htm ) uses some kind of measured value as the first input for the Moran's I function, no matter which library is used (I looked into the ape and spdep packages). However, all I have are the points themselves I want to check the correlation for. The problem is, as funny (or sad) as this might sound, I've no idea what I'm doing here. I'm not much of a (spatial) statistics guy, all I

I have a R script I'm running now that is currently using 3 correlated variables. I'd like to add a 4th, and am wondering if there's a simple way to input matrix data, particularly for correlation matrices---some Matlab-like technique to enter a correlation matrix, 3x3 or 4x4, in R without the linear to matrix reshape I've been using. In Matlab, you can use the semicolon as an end-row delimiter, so it's easy to keep track of where the cross correlations are. In R, where I first create corr <- c(1, 0.1, 0.5, 0.1, 1, 0.9, 0.5, 0.9, 1) cormat <- matrix(corr, ncol=3) Versus cormat = [1 0.1 0.5; 0

I would like to know if anyone knows how to perform a cross-correlation between two audio signals on iOS . I would like to align the FFT windows that I get at the receiver (I am receiving the signal from the mic) with the ones at the transmitter (which is playing the audio track), i.e. make sure that the first sample of each window (besides a "sync" period) at the transmitter will also be the first window at the receiver. I injected in every chunk of the transmitted audio a known waveform (in the frequency domain). I want estimate the delay through cross-correlation between the known waveform