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I have 2 series of variables, I want to plot the probability density function of these 2 variabels (i.e. two curves in one graph), I just want to compare these two variable distribution. what should I do? can I use ggplot2 package? -- View this message in context: http://r.789695.n4.nabble.com/plot-probability-density-function-pdf-tp3897055p3897055.html Sent from the R help mailing list archive

Dear all, I have a lot of problems on R-programming. for example my csv. file is .. Date wrfRH wrfsolar wrfwindspeed wrfrain wrftd wrfta 21/10/2010 92.97 22.11 53.27 0 1546.337861 61.00852664 22/10/2010 87.35 21.99 40.89 0 1300.408288 62.85352227 23/10/2010 88.38 21.71 28.04 0.01 1381.768284 54.80594493 24/10/2010 92.32 15.45 22.38 0.51 1113.90981 39.46573663 25/10/2010 93.42

Hi again! I have a question about R. I have done gam in previous version of R with "mgcv" package and saved the workspace. This workspace contains different models and I will do prediction by these GAMs. However, I install new version of R. and use the same workspace. when I type summary(models), and the error message showed Error in Predict.matrix.cr.smooth(object, dk$data) : F is

First of all, I have GAMs noxd<-gam(newNOX~pressure+maxtemp+s(avetemp,bs="cr")+s(mintemp,bs="cr")+s(RH,bs="cr")+s(solar,bs="cr")+s(windspeed,bs="cr")+s(transport,bs="cr"),family=gaussian (link=log),groupD,methods=REML) Then I type " summary(noxd)". and show Family: gaussian Link function: log Formula: newNO2 ~ pressure

I'm new R-programming user, I need to use gam function. y<-gam(a~s(b),family=gaussian(link=log),data) y<-gam(loga~s(b), family =gaussian (link=identity),data) why these two command results are different? I guess these two command results are same, but actally these two command results are different, Why? -- View this message in context:

I'm beginner in R! I have a lot of problems on R..... I have three questions about GAM 1. What is the function of Gaussian distribution in GAM?(if I choose family is Gaussian) Is it used in the predictand value (Y)? 2. How to plot a graph the gam function? For example: y<-gam(a~s(b),family=gaussian (link=log) ,Data) how to plot x axis is s(b) and y axis is log a??? 3. if I use GAM to

i read a book from WOOD, there's an example which is talking about the pollutant. library(gamair) library(mgcv) y<-gam(death~s(time,bs="cr",k=200)+s(pm10median,bs="cr")+s(so2median,bs="cr")+s(o3median,bs="cr")+s(tmpd,bs="cr"),data=chicago,family=Possion) lag.sum<-function(a,10,11) {n<-length(a) b<-rep(0,n-11) for(i in 0:(11-10))

Hi everyone! I have a simple question. my data is predict_SO2_a 1 39.793231 2 30.252578 3 32.467584 4 31.941509 5 27.908320 6 11.594137 7 9.368125 8 12.319093 9 11.558811 10 7.937192 11 11.211306 12 12.400342 13 12.393146 14 13.256160 15 10.709600 16 9.966334 17 28.850652 18 10.024405 I want

i use "mgcv" package First, what is the different between partial response and partial residual plot? actually, is it partial response is as same as partial regression? second, if I use "log-link fuction", how to plot partial response and partial residual plot by R? Finally, If I want to plot partial resonse and partial residual plot, Should I create new gam equation by

I have 5 GAMs ( model1, model2, model3, model4 and model5) Before I use some data X(predictor -January to June data) to form a equation and calculate the expected value of Y (predictand -January to June). After variable selection, GAMs (Model 1)were bulit up! R-square :0.40 NOW, I want to use new X'( predictor -July - December data) and put into Model 1, then get the expected value of Y'

hi! I hope all of you can help me this question for example GAMs: ozonea<-gam(newozone~ pressure+maxtemp+s(avetemp,bs="cr")+s(ratio,bs="cr"),family=gaussian (link=log),groupA,methods=REML) formula(ozonea) newozone ~ pressure + maxtemp + s(avetemp, bs = "cr") + s(ratio,bs = "cr") #formula of gams coef(ozonea) # extract the coefficient of GAMs

Dear all, I find some troubles about how to extact the row from csv. file by using if-statement condition. I want to extract the row if the rainfall is greater than the mean of rainfall and using the wrfta divided into 3 groups that's rainfall greater than mean -> group A ( create file group A_rain) -> groupB ( create file group B_rain)