search for: noela

 Dear All   let me go one step further by asking you if you could help me show that the distribution of this data in normal.  have a little idea (by trial and error) but i seem to not fully understand how its done.   H<-rnorm(100, mean=50000, sd=3000) par(las=1) hist(H, breaks=seq(40000, 60000, 1000), freq=F) f<- function(x) exp(-(x-5000)^2/18000000)/sqrt(18000000*pi)  x<- seq(40000,

...3]*x^2+coef[4]*x^3 How can i avoid to write the values of the coefficients by hand?? I need to do this many many times, this is the reason i need to be able to automate the process and then build a loop to repeat it many times with different outputs of a linear model! Somebody can help me? -- Noela Grupo de Recursos Marinos y Pesquerías Universidad de A Coruña [[alternative HTML version deleted]]

Hi, I'm trying to perform a Principal Component Analysis on meteorological data with 10 predictors. I use the library pcaMethods to obtain a lot of information (loadings, scores, mean, standard deviation, etc). How can I obtain the scores (new PC variables) for new values of weather predictors using the results of PCA analysis (loadings, mean value, standard deviation) and without