www.gusucode.com > econ 案例源码程序 matlab代码 > econ/SARMAErrorModelWithoutanInterceptExample.m
%% SARMA Error Model Without an Intercept % This example shows how to specify a regression model with SARMA errors % without a regression intercept. % Copyright 2015 The MathWorks, Inc. %% % Specify the default regression model with % $\rm{SARMA}(1,1)\times(2,1,1)_4$ errors: % % $$\begin{array}{c}{y_t} = {X_t}\beta + {u_t}\\\left( {1 - {a_1}L} \right)\left( {1 - {A_4}{L^4} - {A_8}{L^8}} \right)\left( {1 - {L^4}} \right){u_t} = \left( {1 + {b_1}L} \right)\left( {1 + {B_4}{L^4}} \right){\varepsilon _t}.\end{array}$$ % Mdl = regARIMA('ARLags',1,'SARLags',[4, 8],... 'Seasonality',4,'MALags',1,'SMALags',4,'Intercept',0) %% % The name-value pair argument: % % * |'ARLags',1| specifies which lags have nonzero coefficients in the nonseasonal % autoregressive polynomial, so $a(L) = (1 - a_1L)$. % * |'SARLags',[4 8]| specifies which lags have nonzero coefficients in % the seasonal autoregressive polynomial, so $A(L) = (1 - A_4L^4 - A_8L^8)$. % * |'MALags',1| specifies which lags have nonzero coefficients in the nonseasonal % moving average polynomial, so $b(L) = (1 + b_1L)$. % * |'SMALags',4| specifies which lags have nonzero coefficients in the % seasonal moving average polynomial, so $B(L) = (1 + B_4L^4)$. % * |'Seasonality',4| specifies the degree of seasonal integration and corresponds % to $(1 - L^4)$. % %% % The software sets |Intercept| to 0, but all other parameters in |Mdl| % are |NaN| values by default. %% % Property |P| = _p_ + _D_ + $p_s$ + s = 1 + 0 + 8 + 4 = 13, and property % |Q| = _q_ + $q_s$ = 1 + 4 = 5. Therefore, the software requires at least % 13 presample observation to initialize |Mdl|. %% % Since |Intercept| is not a |NaN|, it is an equality constraint during % estimation. In other words, if you pass |Mdl| and data into |estimate|, % then |estimate| sets |Intercept| to 0 during estimation. % % You can modify the properties of |Mdl| using dot notation. % % Be aware that the regression model intercept (|Intercept|) is not identifiable % in regression models with ARIMA errors. If you want to estimate |Mdl|, % then you must set |Intercept| to a value using, for example, dot notation. % Otherwise, |estimate| might return a spurious estimate of |Intercept|.