def multiReg(x, y, colList, alpha):
#d = rpy.r.data_frame(y)
newX = []
d = {'Y':y}
model_string = "Y~"
#names = ["Y"]
for i in colList:
name = "X" + str(i)
#names.append( name )
d[name] = x[i]
newX.append(x[i])
model_string = model_string + name + "+"
print d
#rpy.r.colnames(d) = names
model_string = model_string + "1"
model = rpy.r(model_string)
n = rpy.sqrt( len( y ) )
norm = rpy.r.qnorm( 1. - ( alpha/200. ) )
Rlm = rpy.with_mode(rpy.NO_CONVERSION, rpy.r.lm)
reg = Rlm(model, data = d)
result = rpy.r.summary(reg)
print result
coef =result['coefficients']
r2 = result['r.squared']
r2adj = result['adj.r.squared']
ic = result['sigma']*norm/n
regressor = coef[:, 0]
data = {'regressor':regressor[1:], 'intercept':regressor[0], 'r2':r2, 'adj_r2':r2adj, 'ic':ic, 'x':newX, 'y':y}
return data
def regression(x, y, regmodel, alpha):
d = rpy.r.data_frame(X=x, Y=y)
model = regmodel
#reg = rpy.r.lm(model, data = d)
n = rpy.sqrt(len(x))
norm = rpy.r.qt(1. - (alpha / 200.), len(x))
Rlm = rpy.with_mode(rpy.NO_CONVERSION, rpy.r.lm)
reg2 = Rlm(model, data=d)
result = rpy.r.summary(reg2)
coef = result['coefficients']
r2 = result['r.squared']
r2adj = result['adj.r.squared']
ic = result['sigma'] * norm / n
try:
slope = coef[1][0]
intercept = coef[0][0]
except IndexError:
slope = coef[0][0]
intercept = 0
data = {
'slope': slope,
'intercept': intercept,
'r2': r2,
'adj_r2': r2adj,
'ic': ic,
'x': x,
'y': y
}
return data
def multiReg(x, y, colList, alpha):
#d = rpy.r.data_frame(y)
newX = []
d = {'Y': y}
model_string = "Y~"
#names = ["Y"]
for i in colList:
name = "X" + str(i)
#names.append( name )
d[name] = x[i]
newX.append(x[i])
model_string = model_string + name + "+"
print d
#rpy.r.colnames(d) = names
model_string = model_string + "1"
model = rpy.r(model_string)
n = rpy.sqrt(len(y))
norm = rpy.r.qnorm(1. - (alpha / 200.))
Rlm = rpy.with_mode(rpy.NO_CONVERSION, rpy.r.lm)
reg = Rlm(model, data=d)
result = rpy.r.summary(reg)
print result
coef = result['coefficients']
r2 = result['r.squared']
r2adj = result['adj.r.squared']
ic = result['sigma'] * norm / n
regressor = coef[:, 0]
data = {
'regressor': regressor[1:],
'intercept': regressor[0],
'r2': r2,
'adj_r2': r2adj,
'ic': ic,
'x': newX,
'y': y
}
return data
def regression(x, y, regmodel, alpha ):
d = rpy.r.data_frame(X=x, Y=y)
model = regmodel
#reg = rpy.r.lm(model, data = d)
n = rpy.sqrt( len( x ) )
norm = rpy.r.qt( 1. - ( alpha/200. ), len(x) )
Rlm = rpy.with_mode(rpy.NO_CONVERSION, rpy.r.lm)
reg2 = Rlm(model, data = d)
result = rpy.r.summary(reg2)
coef = result['coefficients']
r2 = result['r.squared']
r2adj = result['adj.r.squared']
ic = result[ 'sigma' ]*norm/n
try:
slope = coef[1][0]
intercept = coef[0][0]
except IndexError :
slope = coef[0][0]
intercept = 0
data = {'slope':slope, 'intercept':intercept, 'r2':r2,
'adj_r2':r2adj, 'ic':ic, 'x':x, 'y':y}
return data
