On Tue, 2011-04-19 at 17:01 -0700, Ayuni Sena wrote:
Muito obrigada Meninos! Bem lembrado Benilton....o que eu quero é fazer o ajuste simultaneo da matrix Y em função da matriz X agradeço a atenção de voces. Ayuni
É por isso que sugeri o systemfit, vejam o exemplo com apenas um modificação Codigo: require('systemfit') data("Kmenta") attach(Kmenta) eqDemand <- consump ~ price + income eqSupply <- consump ~ price + farmPrice + trend eqSystem <- list(demand = eqDemand, supply = eqSupply) fitols <- systemfit(eqSystem) summary(fitols) resposta: systemfit results method: OLS N DF SSR detRCov OLS-R2 McElroy-R2 system 40 33 155.883 4.43485 0.709298 0.557559 N DF SSR MSE RMSE R2 Adj R2 demand 20 17 63.3317 3.72539 1.93013 0.763789 0.735999 supply 20 16 92.5511 5.78444 2.40509 0.654807 0.590084 The covariance matrix of the residuals demand supply demand 3.72539 4.13696 supply 4.13696 5.78444 The correlations of the residuals demand supply demand 1.000000 0.891179 supply 0.891179 1.000000 OLS estimates for 'demand' (equation 1) Model Formula: consump ~ price + income Estimate Std. Error t value Pr(>|t|) (Intercept) 99.8954229 7.5193621 13.28509 2.0906e-10 *** price -0.3162988 0.0906774 -3.48818 0.0028153 ** income 0.3346356 0.0454218 7.36729 1.0999e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 1.930127 on 17 degrees of freedom Number of observations: 20 Degrees of Freedom: 17 SSR: 63.33165 MSE: 3.725391 Root MSE: 1.930127 Multiple R-Squared: 0.763789 Adjusted R-Squared: 0.735999 OLS estimates for 'supply' (equation 2) Model Formula: consump ~ price + farmPrice + trend Estimate Std. Error t value Pr(>|t|) (Intercept) 58.2754312 11.4629099 5.08383 0.00011056 *** price 0.1603666 0.0948839 1.69013 0.11038810 farmPrice 0.2481333 0.0461879 5.37226 6.2274e-05 *** trend 0.2483023 0.0975178 2.54623 0.02156713 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 2.405087 on 16 degrees of freedom Number of observations: 20 Degrees of Freedom: 16 SSR: 92.551058 MSE: 5.784441 Root MSE: 2.405087 Multiple R-Squared: 0.654807 Adjusted R-Squared: 0.590084 fim da reposta Obs você pode usar outras formas de ajuste com SURE por exemplo -- []s Tura