Merge branch 'pysal_gwr' of github.com:TaylorOshan/crankshaft into pysal_gwr
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@@ -59,9 +59,8 @@ def gwr(subquery, dep_var, ind_vars,
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stand_errs = model.bse.reshape((-1))
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predicted = np.repeat(model.predy.reshape((-1,)), k+1)
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residuals = np.repeat(model.resid_response.reshape((-1,)), k+1)
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r_squared = np.tile(model.localR2.reshape((-1,)), k+1)
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r_squared = np.repeat(model.localR2.reshape((-1,)), k+1)
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rowid = np.tile(rowid, k+1).reshape((-1,))
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var_name = np.tile(ind_vars, k+1).reshape((-1,))
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return zip(coefficients, stand_errs, t_vals, predicted,
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residuals, r_squared, rowid)
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ind_vars.insert(0, 'intercept')
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var_name = np.tile(ind_vars, n).reshape((-1,))
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return zip(coefficients, stand_errs, t_vals, predicted, residuals, r_squared, rowid, var_name)
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@@ -4,7 +4,7 @@ Diagnostics for estimated gwr modesl
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__author__ = "Taylor Oshan tayoshan@gmail.com"
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import numpy as np
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from pysal.contrib.glm.family import Gaussian, Poisson, Binomial
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from crankshaft.regression.glm.family import Gaussian, Poisson, Binomial
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def get_AICc(gwr):
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"""
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@@ -10,10 +10,10 @@ from scipy.stats import t
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from kernels import *
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from diagnostics import get_AIC, get_AICc, get_BIC
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import pysal.spreg.user_output as USER
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from pysal.contrib.glm.family import Gaussian, Binomial, Poisson
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from pysal.contrib.glm.glm import GLM, GLMResults
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from pysal.contrib.glm.iwls import iwls
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from pysal.contrib.glm.utils import cache_readonly
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from crankshaft.regression.glm.family import Gaussian, Binomial, Poisson
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from crankshaft.regression.glm.glm import GLM, GLMResults
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from crankshaft.regression.glm.iwls import iwls
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from crankshaft.regression.glm.utils import cache_readonly
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fk = {'gaussian': fix_gauss, 'bisquare': fix_bisquare, 'exponential': fix_exp}
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ak = {'gaussian': adapt_gauss, 'bisquare': adapt_bisquare, 'exponential': adapt_exp}
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@@ -11,7 +11,7 @@ __author__ = "Taylor Oshan Tayoshan@gmail.com"
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from kernels import *
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from search import golden_section, equal_interval, flexible_bw
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from gwr import GWR
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from pysal.contrib.glm.family import Gaussian, Poisson, Binomial
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from crankshaft.regression.glm.family import Gaussian, Poisson, Binomial
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import pysal.spreg.user_output as USER
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from diagnostics import get_AICc, get_AIC, get_BIC, get_CV
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from scipy.spatial.distance import pdist, squareform
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