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- Bugfixes in naive, arima and quantreg and optimizations on benchmarks

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Petrônio Cândido de Lima e Silva 2017-05-09 19:03:53 -03:00
parent 18b69fa71f
commit 5f7c0f0bfa
1 changed files with 5 additions and 4 deletions
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9
benchmarks/arima.py
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@ -35,7 +35,8 @@ class ARIMA(fts.FTS):
try: try:
self.model = stats_arima(data, order=(self.p, self.d, self.q)) self.model = stats_arima(data, order=(self.p, self.d, self.q))
self.model_fit = self.model.fit(disp=0) self.model_fit = self.model.fit(disp=0)
except: except Exception as ex:
print(ex)
self.model_fit = None self.model_fit = None
def ar(self, data): def ar(self, data):
@ -55,14 +56,14 @@ class ARIMA(fts.FTS):
ret = [] ret = []
if self.d == 0: if self.d == 0:
ar = np.array([self.ar(ndata[k - self.p: k]) for k in np.arange(self.p, l)]) ar = np.array([self.ar(ndata[k - self.p: k]) for k in np.arange(self.p, l+1)]) #+1 to forecast one step ahead given all available lags
else: else:
ar = np.array([ndata[k] + self.ar(ndata[k - self.p: k]) for k in np.arange(self.p, l)]) ar = np.array([ndata[k] + self.ar(ndata[k - self.p: k]) for k in np.arange(self.p, l+1)])
if self.q > 0: if self.q > 0:
residuals = np.array([ndata[k] - ar[k - self.p] for k in np.arange(self.p, l)]) residuals = np.array([ndata[k] - ar[k - self.p] for k in np.arange(self.p, l)])
ma = np.array([self.ma(residuals[k - self.q: k]) for k in np.arange(self.q, len(residuals))]) ma = np.array([self.ma(residuals[k - self.q: k]) for k in np.arange(self.q, len(residuals)+1)])
ret = ar[self.q:] + ma ret = ar[self.q:] + ma
else: else: