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Consider the following missing data problem: y = c(1, 2, 2, 2, 3) a = factor(c(1, 1, 1, 2, 2)) b = factor(c(1, 2, 3, 1, 2)) fit = lm(y ~ a + b) anova(fit) Analysis of Variance Table Response: y Df Sum Sq Mean Sq F value Pr(>F) a 1 0.83333 0.83333 1.3637e+33 < 2.2e-16 *** b 2 1.16667 0.58333 9.5461e+32 < 2.2e-16 *** Residuals 1 0.00000 0.00000 ---

Hi. I know that R computes sums of squares based on the diagonal of t(Q) %*% y %*% t(y) %*% Q, where Q comes from the QR-decomposition of the model matrix. Does anyone know where I can find a proof for this result? All Best and Happy New Year, Ethan [[alternative HTML version deleted]]

Hi. I want to create a plot with Pantone654 as the background. The RGB for this color is (0,61,121), which corresponds to a hex of #003D79. How do I specify the bg parameter for this? All Best, Ethan [[alternative HTML version deleted]]

Hi. I want to use the text() command to produce graphics text in the (Windows) font Tahoma, but I don't know how to do this. I appreciate any suggestions/ideas you may have. All Best, Ethan [[alternative HTML version deleted]]

Hi. I am trying to analyze with BRugs the Box-Tiao variance components example in WinBUGS. The output from BRugs, mean sd MC_error val2.5pc median val97.5pc start sample sigma2.btw 681.9 1161 10.89 0.7016 253.8 4232 25001 100000 sigma2.with 4266.0 1246 4.92 2480.0000 4057.0 7262 25001 100000 doesn't match the output from WinBUGS, node mean