def lmer_series(dm, formula, winlen=1):
col = formula.split()[0]
depth = dm[col].depth
rm = None
for i in range(0, depth, winlen):
wm = dm[:]
wm[col] = series.reduce_(
series.window(wm[col], start=i, end=i+winlen))
lm = lmer(wm, formula)
print('Sample %d' % i)
print(lm)
if rm is None:
rm = DataMatrix(length=len(lm))
rm.effect = list(lm.effect)
rm.p = SeriesColumn(depth=depth)
rm.t = SeriesColumn(depth=depth)
rm.est = SeriesColumn(depth=depth)
rm.se = SeriesColumn(depth=depth)
for lmrow, rmrow in zip(lm, rm):
rmrow.p[i:i+winlen] = lmrow.p
rmrow.t[i:i+winlen] = lmrow.t
rmrow.est[i:i+winlen] = lmrow.est
rmrow.se[i:i+winlen] = lmrow.se
return rm
def glmer_series(dm, formula, family, winlen=1):
col = formula.split()[0]
depth = dm[col].depth
rm = None
for i in range(0, depth, winlen):
wm = dm[:]
wm[col] = series.reduce_(
series.window(wm[col], start=i, end=i + winlen))
lm = glmer(wm, formula, family=family)
print('Sample %d' % i)
print(lm)
if rm is None:
rm = DataMatrix(length=len(lm))
rm.effect = list(lm.effect)
rm.p = SeriesColumn(depth=depth)
rm.z = SeriesColumn(depth=depth)
rm.est = SeriesColumn(depth=depth)
rm.se = SeriesColumn(depth=depth)
for lmrow, rmrow in zip(lm, rm):
rmrow.p[i:i + winlen] = lmrow.p
rmrow.z[i:i + winlen] = lmrow.z
rmrow.est[i:i + winlen] = lmrow.est
rmrow.se[i:i + winlen] = lmrow.se
return rm
