第14章时间序列分析 nalysIs
第14章 时间序列分析 Time-Series Analysis
本章概要 Component Factors of the Time-Series model Smoothing of Data Series 口 Moving averages a Exponential Smoothing Least square Trend Fitting and forecasting a Linear, Quadratic and Exponential Models Autoregressive models Choosing Appropriate models Monthly or Quarterly data
本章概要 • Component Factors of the Time-Series Model • Smoothing of Data Series Moving Averages Exponential Smoothing • Least Square Trend Fitting and Forecasting Linear, Quadratic and Exponential Models • Autoregressive Models • Choosing Appropriate Models • Monthly or Quarterly Data
What Is Time-series A Quantitative Forecasting Method to Predict Future values Numerical Data Obtained at regular Time Intervals Projections Based on Past and Present Observations Example: Year:19941995199619971998 aes 75.374.278.579780.2
What Is Time-Series • A Quantitative Forecasting Method to Predict Future Values • Numerical Data Obtained at Regular Time Intervals • Projections Based on Past and Present Observations • Example: Year:1994 1995 1996 1997 1998 Sales: 75.3 74.2 78.5 79.7 80.2
Time-Series Components 时间序列的组成 Trend Cyclical Time-Series Seasonal Random
Time-Series Components 时间序列的组成 Time-Series Cyclical Random Trend Seasonal
Trend Component 趋势项 Overall Upward or Downward movement Data Taken over a period of years Sales Upward trend Time
Trend Component 趋势项 • Overall Upward or Downward Movement • Data Taken Over a Period of Years Sales Time