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Hi, I was hoping to clarify the exact behavior associated with this incantation: validate(fit.ols, method='cross', B=50) Output: index.orig training test optimism index.corrected n R-square 0.5612 0.5613 0.5171 0.0442 0.5170 50 MSE 1.3090 1.3086 1.3547 -0.0462 1.3552 50 Intercept 0.0000 0.0000 -0.0040 0.0040

I have two assignment problems... I have written this small code for regression with two regressors . n <- 50 x1 <- runif(n,1,10) x2 <- x1 + rnorm(n,0,0.5) plot(x1,x2) # x1 and x2 strongly correlated cor(x1,x2) y <- 3 + 0.5*x1 + 1.1*x2 + rnorm(n,0,2) intact.lm <- lm(y ~ x1 + x2) summary(intact.lm) anova(intact.lm) the questions are 1.The function summary() is convenient since

I have two assignment problems... I have written this small code for regression with two regressors . n <- 50 x1 <- runif(n,1,10) x2 <- x1 + rnorm(n,0,0.5) plot(x1,x2) # x1 and x2 strongly correlated cor(x1,x2) y <- 3 + 0.5*x1 + 1.1*x2 + rnorm(n,0,2) intact.lm <- lm(y ~ x1 + x2) summary(intact.lm) anova(intact.lm) the questions are 1.The function summary() is convenient since

Hi everyone,   I'm trying to do an Logistic Politomic Regression in R. Because I have my resposes variables and the aswer is 0 and 1 in 3 bacterial genes. Somebody know how to do this in R in a easy way?   Thank so much,   José Bustos Facultad de Ciencias Universidad Catolica Ssma. Concepcion Chile --- El lun, 31/8/09, r-help-request@r-project.org <r-help-request@r-project..org>