[시계열 분석] AR, MA 실습

2022.10.30 - [분류 전체보기] - [시계열 분석] 자기회귀 모델(AR)

2022.10.30 - [분류 전체보기] - [시계열 분석] 이동 평균 모델 (MA)

 

 

< AR >

from pandas import read_csv
from matplotlib import pyplot
from statsmodels.tsa.ar_model import AutoReg
from sklearn.metrics import mean_squared_error
from math import sqrt

# 데이터 로드
df = read_csv('AirPassengers.csv')

# 학습, 테스트 데이터 분리
X = df['#Passengers'].values
train, test = X[1:int(len(X)*0.7)], X[int(len(X)*0.7):]

# 자기회귀모형 학습
model = AutoReg(train, lags=12)
model_fit = model.fit()

# prediction
predictions = model_fit.predict(start=len(train), end=len(train)+len(test)-1, dynamic=False)
rmse = sqrt(mean_squared_error(test, predictions))

# 그래프
pyplot.plot(test)
pyplot.plot(predictions, color='red')
pyplot.show()

 

 

< MA >

from statsmodels.tsa.arima_model import ARMA

# MA(1)
model_ma_1 = ARMA(train, order = (0,1))
result_ma_1 = model_ma_1.fit()
result_ma_1.summary()

 

 

 

 

[참고]

https://ko.code-paper.com/python/examples-ar-model-python

https://direction-f.tistory.com/67