Practical-Time-Series-Analysis:实用时间序列分析，由Packt发布

[{"title":"（ 51 个子文件 2.94MB ） Practical-Time-Series-Analysis:实用时间序列分析，由Packt发布","children":[{"title":"Practical-Time-Series-Analysis-master","children":[{"title":"Chapter01","children":[{"title":"Chapter_1_Different_Types_of_Data.ipynb <span style='color:#111;'> 181.67KB </span>","children":null,"spread":false},{"title":"Chapter_1_Models_for_Time_Series_Analysis.ipynb <span style='color:#111;'> 75.71KB </span>","children":null,"spread":false},{"title":"Chapter_1_Internal_Structures.ipynb <span style='color:#111;'> 222.81KB </span>","children":null,"spread":false},{"title":"Chapter_1_Autocorrelation.ipynb <span style='color:#111;'> 79.00KB </span>","children":null,"spread":false}],"spread":true},{"title":".gitattributes <span style='color:#111;'> 378B </span>","children":null,"spread":false},{"title":"Chapter05","children":[{"title":"Chapter_5_PM2.5_Time_Series_Forecasting_by_MLP.ipynb <span style='color:#111;'> 230.32KB </span>","children":null,"spread":false},{"title":"Chapter_5_PM2.5_Time_Series_Forecasting_by_1D_Convolution.ipynb <span style='color:#111;'> 255.09KB </span>","children":null,"spread":false},{"title":"Chapter_5_Air_Pressure_Time_Series_Forecasting_by_1D_Convolution.ipynb <span style='color:#111;'> 187.19KB </span>","children":null,"spread":false},{"title":"Chapter_5_Air Pressure_Time_Series_Forecasting_by_LSTM.ipynb <span style='color:#111;'> 188.91KB </span>","children":null,"spread":false},{"title":"Chapter_5_PM2.5_Time_Series_Forecasting_by_LSTM.ipynb <span style='color:#111;'> 251.23KB </span>","children":null,"spread":false},{"title":"Chapter_5_PM2.5_Time_Series_Forecasting_by_GRU.ipynb <span style='color:#111;'> 251.78KB </span>","children":null,"spread":false},{"title":"Chapter_5_Air Pressure_Time_Series_Forecasting_by_GRU.ipynb <span style='color:#111;'> 189.83KB </span>","children":null,"spread":false},{"title":"Chapter_5_Air Pressure_Time_Series_Forecasting_by_MLP.ipynb <span style='color:#111;'> 189.57KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter04","children":[{"title":"Chapter_4_AR.py <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"Chapter_4_MA.py <span style='color:#111;'> 1.51KB </span>","children":null,"spread":false},{"title":"Chapter_4_ARMA_IBMstock.py <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"Chapter_4_ARMA.py <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"Chapter_4_ARIMA.py <span style='color:#111;'> 4.26KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter03","children":[{"title":"Chapter_3_simpleExponentialSmoothing.py <span style='color:#111;'> 2.17KB </span>","children":null,"spread":false},{"title":"Chapter_3_decomposition.py <span style='color:#111;'> 558B </span>","children":null,"spread":false},{"title":"Chapter_3_tripleExponentialSmoothing.py <span style='color:#111;'> 2.60KB </span>","children":null,"spread":false},{"title":"Chapter_3_doubleExponentialSmoothing.py <span style='color:#111;'> 3.01KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chapter02","children":[{"title":"Chapter_2_Seasonality_Adjustment_by_Moving_Averages.ipynb <span style='color:#111;'> 173.23KB </span>","children":null,"spread":false},{"title":"Chapter_2_Time_Series_Decomposition_by_Moving_Averages.ipynb <span style='color:#111;'> 119.13KB </span>","children":null,"spread":false},{"title":"Chapter_2_Augmented_Dickey_Fuller_Test.ipynb <span style='color:#111;'> 43.04KB </span>","children":null,"spread":false},{"title":"Chapter_2_First_Order_Differencing.ipynb <span style='color:#111;'> 108.14KB </span>","children":null,"spread":false},{"title":"Chapter_2_Seasonal_Differencing.ipynb <span style='color:#111;'> 140.68KB </span>","children":null,"spread":false},{"title":"Chapter_2_Moving_Averages.ipynb <span style='color:#111;'> 95.83KB </span>","children":null,"spread":false},{"title":"Chapter_2_Data_Processing_and_Visualization.ipynb <span style='color:#111;'> 181.80KB </span>","children":null,"spread":false},{"title":"Chapter_2_Seasonal_Differencing-AutoCorr_Plot_Correction.ipynb <span style='color:#111;'> 219.18KB </span>","children":null,"spread":false},{"title":"Chapter_2_Time_Series_Decomposition_using_statsmodels.ipynb <span style='color:#111;'> 122.76KB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 2.27KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 649B </span>","children":null,"spread":false},{"title":"Data Files","children":[{"title":"us-airlines-monthly-aircraft-miles-flown.csv <span style='color:#111;'> 1.70KB </span>","children":null,"spread":false},{"title":"DJIA_Jan2016_Dec2016.xlsx <span style='color:#111;'> 22.44KB </span>","children":null,"spread":false},{"title":"mean-daily-temperature-fisher-river.xlsx <span style='color:#111;'> 30.52KB </span>","children":null,"spread":false},{"title":"PRSA_data_2010.1.1-2014.12.31.csv <span style='color:#111;'> 1.92MB </span>","children":null,"spread":false},{"title":"World Bank Mobile Phone Statistics.xlsx <span style='color:#111;'> 45.72KB </span>","children":null,"spread":false},{"title":"quarterly-beer-production-in-aus-March 1956-June 1994.csv <span style='color:#111;'> 2.57KB </span>","children":null,"spread":false},{"title":"ibm-common-stock-closing-prices.csv <span style='color:#111;'> 19.20KB </span>","children":null,"spread":false},{"title":"monthly-mean-thickness-dobson-un.csv <span style='color:#111;'> 7.76KB </span>","children":null,"spread":false},{"title":"mean-daily-temperature-fisher-river.csv <span style='color:#111;'> 23.39KB </span>","children":null,"spread":false},{"title":"inflation-consumer-prices-annual.xlsx <span style='color:#111;'> 10.09KB </span>","children":null,"spread":false},{"title":"monthly-sunspot-number-zurich-17.csv <span style='color:#111;'> 44.06KB </span>","children":null,"spread":false},{"title":"Data Files <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"DJIA_May2016_May2017.csv <span style='color:#111;'> 19.51KB </span>","children":null,"spread":false},{"title":"Annual_Number_of_Lynx_trapped.csv <span style='color:#111;'> 1.51KB </span>","children":null,"spread":false},{"title":"chemical-concentration-readings.csv <span style='color:#111;'> 4.98KB </span>","children":null,"spread":false},{"title":"wisconsin-employment-time-series.csv <span style='color:#111;'> 2.58KB </span>","children":null,"spread":false},{"title":"Monthly_CO2_Concentrations.xlsx <span style='color:#111;'> 11.88KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}],"spread":true}]