Software Listing of Author : "Adam Auton"
- LDhat
- License: Freeware
- Price: 0.00


LDhat is a C/C++ written project that was specially designed for the analysis of recombination rates from population genetic data.
The following programs are included:
· convert: Simple manipulation of DNA sequence data
· pairwise: Parametric and nonparametric analyses of recombination
· interval: Estimation of variable recombination rates
· rhomap: Estimation of variable recombination rates in the presence of hotspots
· fin : Simulation of genetic variation data
- Publisher: Adam Auton
- Date Released:
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- Platform: WinOther
- Median Polish
- License: Shareware
- Price:


MEDIAN_POLISH(X) fits an additive model to a 2D input matrix, X, assuming a decomposition of (constant + rows + columns). Median polishing is useful for removing spatial trends in the data by alternately removing medians from the rows and columns of the data. The algorithm proceeds as follows. Considering the rows first, for each row the row median is subtracted from every element in that row. Then, for each column, the median of the revised numbers is then subtracted from every element in that column. This process is repeated until all convergence, or a maximum number of iterations.
- Publisher: Adam Auton
- Date Released: 06-03-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- Normalised Partial Energy Sequence
- License: Freeware
- Price: 0.00


alculate the normalized partial energy sequence (NPES) for a given signal vector X. If a particular transform is capable of capturing the key features of a signal in few coefficients, the NPES will approach unity for relatively quickly. Ref: Percival and Walden, Wavelet Methods for Time Series Analysis, 2000. Pg 130.
- Publisher: Adam Auton
- Date Released: 03-04-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
- wmean
- License: Shareware
- Price:


For vectors, WMEAN(X,W) is the weighted mean value of the elements in X using non-negative weights W. For matrices, WMEAN(X,W) is a row vector containing the weighted mean value of each column. For N-D arrays, WMEAN(X,W) is the weighted mean value of the elements along the first non-singleton dimension of X. Class support for inputs X and W: float: double, single Example: x = rand(5,2); w = rand(5,2); wmean(x,w)
- Publisher: Adam Auton
- Date Released: 02-06-2013
- Download Size: 10 KB
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- Platform: Matlab, Scripts
