tailieunhanh - SAS/ETS 9.22 User's Guide 176

SAS/Ets User's Guide 176. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 1742 F Chapter 26 The STATESPACE Procedure That is start by considering whether to add x1 t 1 t to the initial state vector z1. The procedure forms the submatrix V1 that corresponds to f and computes its canonical correlations. Denote the smallest canonical correlation of V1 as pmin. If Pmin is significantly greater than 0 x1 t 1 t is added to the state vector. If the smallest canonical correlation of V1 is not significantly greater than 0 then a linear combination of f is uncorrelated with the past pt. Assuming that the determinant of Co is not 0 that is no input series is a constant you can take the coefficient of x1 t 1 t in this linear combination to be 1. Denote the coefficients of z in this linear combination as . This gives the relationship X1 t 1 t xt Therefore the current state vector already contains all the past information useful for predicting x1 t i and any greater leads of x1 t. The variable x1 t 1 t is not added to the state vector nor are any terms x1 t k t considered as possible components of the state vector. The variable x1 is no longer active for state vector selection. The process described for x1 t 1 t is repeated for the remaining elements of ft. The next candidate for inclusion in the state vector is the next component of ft that corresponds to an active variable. Components of ft that correspond to inactive variables that produced a zero pmin in a previous step are skipped. Denote the next candidate as xi t k t. The vector fj is formed from the current state vector and xi t kjt as follows fj .zj xi t k t y The matrix Vj is formed from f j and its canonical correlations are computed. The smallest canonical correlation of Vj is judged to be either greater than or equal to 0. If it is judged to be greater than 0 xijt k t is added to the state vector. If it is judged to be 0 then a linear combination of fj is uncorrelated with the pt and the variable xi is now inactive. The state vector selection process continues until no active variables .

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• Hướng dẫn sử dụng SAS ETS
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• báo cáo tài chính
• phân tích đầu tư
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