Source code for naginterfaces.​library.​examples.​correg.​lars_param_ex

#!/usr/bin/env python
"``naginterfaces.library.correg.lars_param`` Python Example."

# NAG Copyright 2018-2019.

# pylint: disable=invalid-name,too-many-locals

from naginterfaces.library import correg

[docs]def main(): """ Example for :func:`naginterfaces.library.correg.lars_param`. Least angle regression, additional parameter estimates. >>> main() naginterfaces.library.correg.lars_param Python Example Results. Parameter Estimates from lars_xtx Step Parameter Estimate ----------------------------------------------------------------- 1 0.000 0.000 3.125 0.000 0.000 0.000 2 0.000 0.000 3.792 0.000 0.000 -0.713 3 -0.446 0.000 3.998 0.000 0.000 -1.151 4 -0.628 -0.295 4.098 0.000 0.000 -1.466 5 -1.060 -1.056 4.110 -0.864 0.000 -1.948 6 -1.073 -1.132 4.118 -0.935 -0.059 -1.981 Additional Parameter Estimates from lars_param nk Parameter Estimate ----------------------------------------------------------------- 0.2 0.000 0.000 0.625 0.000 0.000 0.000 1.2 0.000 0.000 3.258 0.000 0.000 -0.143 3.2 -0.483 -0.059 4.018 0.000 0.000 -1.214 4.5 -0.844 -0.676 4.104 -0.432 0.000 -1.707 5.2 -1.062 -1.071 4.112 -0.878 -0.012 -1.955 """ print('naginterfaces.library.correg.lars_param Python Example Results.') n = 20 mtype = 1 m = 6 # Initialize dataset d = [[10.28, 1.77, 9.69, 15.58, 8.23, 10.44], [9.08, 8.99, 11.53, 6.57, 15.89, 12.58], [17.98, 13.10, 1.04, 10.45, 10.12, 16.68], [14.82, 13.79, 12.23, 7.00, 8.14, 7.79], [17.53, 9.41, 6.24, 3.75, 13.12, 17.08], [7.78, 10.38, 9.83, 2.58, 10.13, 4.25], [11.95, 21.71, 8.83, 11.00, 12.59, 10.52], [14.60, 10.09, -2.70, 9.89, 14.67, 6.49], [3.63, 9.07, 12.59, 14.09, 9.06, 8.19], [6.35, 9.79, 9.40, 12.79, 8.38, 16.79], [4.66, 3.55, 16.82, 13.83, 21.39, 13.88], [8.32, 14.04, 17.17, 7.93, 7.39, -1.09], [10.86, 13.68, 5.75, 10.44, 10.36, 10.06], [4.76, 4.92, 17.83, 2.90, 7.58, 11.97], [5.05, 10.41, 9.89, 9.04, 7.90, 13.12], [5.41, 9.32, 5.27, 15.53, 5.06, 19.84], [9.77, 2.37, 9.54, 20.23, 9.33, 8.82], [14.28, 4.34, 14.23, 14.95, 18.16, 11.03], [10.17, 6.80, 3.17, 8.57, 16.07, 15.93], [5.39, 2.67, 6.37, 13.56, 10.68, 7.35]] # Initialize observed values y = [-46.47, -35.80, -129.22, -42.44, -73.51, -26.61, -63.90, -76.73, -32.64, -83.29, -16.31, -5.82, -47.75, 18.38, -54.71, -55.62, -45.28, -22.76, -104.32, -55.94] # Create augmented matrix [d:y] dy = [drow + [yrow] for drow, yrow in zip(d, y)] # Calculate cross product (upper triangle) of augmented matrix dytdy = correg.ssqmat(dy).c # pm = amount of elements in triangle of m x m matrix pm = (m*m+m)//2 # Cross product matrix of d (dtd) is stored in first pm elements dtd = [dytdy[:pm]] # Cross product of d and y (dty) are next m elements dty = dytdy[pm:pm+m] # Last element is sums of squares of y (yty) yty = dytdy[-1] # Fit model ip, nstep, b, fitsum = correg.lars_xtx(mtype, n, dtd, dty, yty) # Calculate addition parameters for intermediate lars steps nk = [0.2, 1.2, 3.2, 4.5, 5.2] nb = correg.lars_param(b, fitsum, 1, nk) print('Parameter Estimates from lars_xtx') print('Step' + ' '*15 + 'Parameter Estimate') sep_len = 5 + ip*10 print('-'*sep_len) for k in range(nstep): print(' ' + str(k+1) + ' ' + ' '.join('{:6.3f}'.format(bi) for bi in b[:ip, k])) print('Additional Parameter Estimates from lars_param') print(' nk ' + ' '*15 + 'Parameter Estimate') sep_len = 5 + ip*10 print('-'*sep_len) for i, v in enumerate(nk): print(' ' + str(v) + ' ' + ' '.join('{:6.3f}'.format(bi) for bi in nb[:ip, i]))
if __name__ == '__main__': import doctest import sys sys.exit( doctest.testmod( None, verbose=True, report=False, optionflags=doctest.REPORT_NDIFF, ).failed )