Contents

1. Time Dependence Studying (p. 1)
   1. Time Series
   2. Estimation Theory
   3. Parameters Estimation through Least Squares Method
   4. Link between Least Squares Method and Others Methods
   5. Time Series Analysis through Correlation Method
   6. Simple Correlation. Linear Regression. Regression Coefficient
   7. Correlation Coefficient. Covariance
   8. Correlation Ratio
   9. Ranks Correlation
   10. Self Correlation
   11. Analysis through Period Diagrams
   12. Correlation Diagram
2. Numeric Analysis of Time Series (p. 23)
   1. Time Series Decomposing
   2. Evolution Tendency. Trend
      1. Linear Regression
      2. Regression through Partial Taylor Series
      3. Parabolic Regression. Hyperbolic Regression
      4. Special Case of Polynomial Trend
      5. Determining the Rank of Polynomial Trend
      6. Nonlinear Regression. Iterative Methods
      7. Exponential Regression and Logarithmic Regression
   3. Seasonality and Periodicity
      1. Seasonality Series
      2. Constructing of Seasonality Series from Harmonic Series
      3. Using of FFT in Constructing of Seasonality Series
      4. Case of Unknown Period. Finding of Series Period
      5. Period Diagram Making. Extracting Information from Period Diagram
   4. Evolution in Time. Prognosis
      1. Stabilization Tendency
      2. Fourier Analysis. Fourier Representation of a Periodic Data String
      3. Parameters Estimation for Cyclic Trend
      4. Harmonic Model for Seasonality Trend
      5. Parseval Theorem. Schuster Spectrogram
      6. Whittaker-Robinson Method
3. Implementation of Time Series Analysis Methods (p. 44)
   1. Implemented Algorithms
   2. Program Sources
   3. Storing, Interface, Graphic Kernel and Portability
   4. Applications
4. References (p. 117)