search for: fittedvalues

...sification problem and have a problem concerning the calculation of the final value for my validation data.(nnet only calculates the final value for the training data). I made my own final value formula (for the training data I get the same value as nnet): # prob-matrix pmatrix <- cat*fittedValues tmp <- rowSums(pmatrix) # -log likelihood finalValue <- sum(-log(tmp)) # add penalty term finalValue + sum(decay * weights^2) where cat is a matrix with cols for each possible category and a row for each data record. The values are 1 for the target categories...

Dear R users, I hope this mailing list be the right place for my question. Usaully performance criterion of curve fitting like as Directinal Symmetry (DS) and Mean Absolute Percentage Error (MAPE) are correctly used with absolute time series which includes only positive values. But how it is possible to use DS and MAPE with other time series like as return series (for example return of a

Dear R-users, I am trying to get a simple plot for a linear model. The following function does the job of getting all the plots of the lm function but the "main" plot. multivarplot <- function(...){ x1 <- rnorm(10); x2 <- rnorm(10); x3 <- rnorm(10) y <- rnorm(10) multivarfit <- lm(y ~ x1 + x2 + x3) par(mfrow = c(3,2)) plot.lm(multivarfit) }