Use Cholesky decomposition to invert

The previous version was using a generic LU inverse, which ran into
numerical stability problems for large q values.  For example,

q=7, c=0, b=(1.40, 1.41, ..., 1.50) looked like:

0.1767019
0.1741197
0.1640931
0.1330334
0.2003187
0.1792207
0.1792029
0.175216
0.1836156
0.2131243
0.2235138

because the source data files have only slight variation in that range.
Using a cholesky decomposition inverse fixes this, and gives numbers
agreeing exactly with JGM's fortran version (which also uses Cholesky
decomposition):

0.1744341
0.1780252
0.181262
0.1841298
0.1866257
0.1887341
0.1904548
0.1917758
0.1926928
0.1932153
0.1933418

which agrees precisely with JGM's (trimmed) fracdist output of:

 P value = 0.174
 P value = 0.178
 P value = 0.181
 P value = 0.184
 P value = 0.187
 P value = 0.189
 P value = 0.190
 P value = 0.192
 P value = 0.193
 P value = 0.193
 P value = 0.193
Added Eigen/Cholesky files
Updated mnfiles hash sum