def __init__(self, modelFile, var='X'):
if isinstance(modelFile, basestring):
x = loadMatVar(modelFile, var)
else:
x = modelFile
x = concatenate((ones((1, shape(x)[1])), x))
xHat = pinv(x)
self.x = x
self.xHat = xHat
def __init__(self, modelFile, var='X'):
if isinstance(modelFile, basestring):
x = loadMatVar(modelFile, var)
else:
x = modelFile
x = concatenate((ones((1, shape(x)[1])), x))
xHat = pinv(x)
self.x = x
self.xHat = xHat
def __init__(self, modelfile, var='X'):
if type(modelfile) is str:
x = loadmatvar(modelfile, var)
else:
x = modelfile
x = concatenate((ones((1, shape(x)[1])), x))
x_hat = pinv(x)
self.x = x
self.x_hat = x_hat
def __init__(self, modelfile, var='X'):
if type(modelfile) is str:
x = loadmatvar(modelfile, var)
else:
x = modelfile
x = concatenate((ones((1, shape(x)[1])), x))
x_hat = pinv(x)
self.x = x
self.x_hat = x_hat
def __init__(self, modelFile, var=('X1', 'X2')):
if isinstance(modelFile, basestring):
x1 = loadMatVar(modelFile[0], var[0])
x2 = loadMatVar(modelFile[1], var[1])
else:
x1 = modelFile[0]
x2 = modelFile[1]
x1Hat = pinv(x1)
self.x1 = x1
self.x2 = x2
self.x1Hat = x1Hat
def __init__(self, modelFile, var=('X1', 'X2')):
if isinstance(modelFile, basestring):
x1 = loadMatVar(modelFile[0], var[0])
x2 = loadMatVar(modelFile[1], var[1])
else:
x1 = modelFile[0]
x2 = modelFile[1]
x1Hat = pinv(x1)
self.x1 = x1
self.x2 = x2
self.x1Hat = x1Hat
def __init__(self, modelfile, var=('X1', 'X2')):
if type(modelfile) is str:
x1 = loadmatvar(modelfile[0], var[0])
x2 = loadmatvar(modelfile[1], var[1])
else:
x1 = modelfile[0]
x2 = modelfile[1]
x1_hat = pinv(x1)
self.x1 = x1
self.x2 = x2
self.x1_hat = x1_hat
def __init__(self, modelfile, var=('X1', 'X2')):
if type(modelfile) is str:
x1 = loadmatvar(modelfile[0], var[0])
x2 = loadmatvar(modelfile[1], var[1])
else:
x1 = modelfile[0]
x2 = modelfile[1]
x1_hat = pinv(x1)
self.x1 = x1
self.x2 = x2
self.x1_hat = x1_hat
def get(self, y):
"""Compute regression coefficients from the second design matrix,
a single r2 statistic, and residuals for the full model"""
b1 = dot(self.x1Hat, y)
b1 = b1 - min(b1)
b1Hat = dot(transpose(self.x1), b1)
if sum(b1Hat) == 0:
b1Hat += 1E-06
x3 = self.x2 * b1Hat
x3 = concatenate((ones((1, shape(x3)[1])), x3))
x3Hat = pinv(x3)
b2 = dot(x3Hat, y)
predic = dot(b2, x3)
resid = y - predic
sse = sum((predic - y)**2)
sst = sum((y - mean(y))**2)
if sst == 0:
r2 = 0
else:
r2 = 1 - sse / sst
return asarray([b2[1:], r2, resid])
def get(self, y):
"""Compute regression coefficients from the second design matrix,
a single r2 statistic, and residuals for the full model"""
b1 = dot(self.x1Hat, y)
b1 = b1 - min(b1)
b1Hat = dot(transpose(self.x1), b1)
if sum(b1Hat) == 0:
b1Hat += 1E-06
x3 = self.x2 * b1Hat
x3 = concatenate((ones((1, shape(x3)[1])), x3))
x3Hat = pinv(x3)
b2 = dot(x3Hat, y)
predic = dot(b2, x3)
resid = y - predic
sse = sum((predic - y) ** 2)
sst = sum((y - mean(y)) ** 2)
if sst == 0:
r2 = 0
else:
r2 = 1 - sse / sst
return asarray([b2[1:], r2, resid])
