similar to: Calculate the angles for a point dataset?

Dear Rusers, I have some data in .csv file like "2004-8-1" and "2004-10-1", and i need to convert them into days from the origin (January 1, 1960). I have tried the function date.mmddyyyy(), but cannot get it. Anybody can show me how to handle the date data? Thanks very much! My dataset like: time 2004-8-1 2004-10-1 2001-9-1 2002-9-1 -- With Kind Regards,

Dear all, Following the help from gam(mgcv) help page, i tried to analyze my dataset with all the default arguments. Unfortunately, it can't be run successfully. I list the errors below. #m.gam<-gam(mark~s(x,y)+s(lstday2004)+s(slope)+s(ndvi2004)+s(elevation)+s(disbinary),family=binomial(logit),data=point)

Dear Rusers, When i start R, there always the following work to do first, how should i cancel it? *--- Please select a CRAN mirror for use in this session ---* I don't know why it does so, maybe i have done something unintentionally. Thanks. -- With Kind Regards, oooO::::::::: (..)::::::::: :\.(:::Oooo:: ::\_)::(..):: :::::::)./::: ::::::(_/:::: :::::::::::::

Dear Rusers, My manuscript has been conditionally accepted recently. The problem to generate the high resolution figures in R for the manuscript cannot be solved by me. The journal editor ask me to generate the figures with a minimum resolution of 500 dpi. I have tried the *menu-driven method* to save the figures as JPEG (100% printed quality), but the results seem not to be very good. I have

Dear friends, The following is an example to explain my question. I want to get a legend which will show the z-values according to different colors in image() function. x<-sort(runif(10)) #x-coordinates y<-sort(runif(10)) #y-coordinates z<-matrix(runif(100),nrow=10) #attributes values image(x,y,z,col=gray((6:3)/6)) # legend(x,y,legend=z,col=gray((6:3)/6)) #error. the colors should

Dear Rusers, I have used R,S-PLUS and SAS to analyze the sample data "bacteria" in MASS package. Their results are listed below. I have three questions, anybody can give me possible answers? Q1:From the results, we see that R get 'NAs'for AIC,BIC and logLik, while S-PLUS8.0 gave the exact values for them. Why? I had thought that R should give the same results as SPLUS here.

Dear R users, I hope to explain the concepts of skewness and kurtosis by generating series of distributions with same skewness and different kurtosis or with same kurtosis and different skewness, but it seems that i cannot find the right functions. I have searched the mailing list, but no answers were found. Is it possible to do that in R? Which function could be used? Thanks a lot. --

Dear friends, My dataset is like the following: x y mcpvalue 0.4603578 0.6247629 1.001 0.4603715 0.6247788 1.001 0.4603852 0.6247948 1.001 0.4110561 0.5664841 0.995 The x and y variables are unsorted. I use the function image(x,y,mcpvalue) to generate a plot, but the error is that "increasing 'x' and

Dear friends, In S-PLUS, we can use the following argument, but not in R. mode12 <- gam(score1 ~ lo(latitude) + lo(longitude)) I searched the help in S-PLUS, it says lo() Allows the user to specify a Loess fit in a GAM formula, but i didn't find the correponding function in R. Anybody knows how to do the similar task in R? Thanks very much. -- With Kind Regards, oooO:::::::::

Dear R users, We have some programs for the specific task in our research, but they were very commonly used. We want to make some functions for them, anybody can recommend any good tools to facilitate us to create R functions even without going deep into the theories of R functions ? Any suggestions or help are greatly appreciated. -- With Kind Regards, oooO::::::::: (..):::::::::

Dear all, I have two variables, y and x. It seems that the relationship between them is Piecewise Linear Functions. The cutpoint is 20. That is, when x<20, there is a linear relationship between y and x; while x>=20, there is another different linear relationship between them. How can i specify their relationships in R correctly? # glm(y~I(x<20)+I(x>=20),family = binomial, data =

Dear Rusers, I am now using R and SAS to fit the piecewise linear functions, and what surprised me is that they have a great differrent result. See below. #R code--Knots for distance are 16.13 and 24, respectively, and Knots for y are -0.4357 and -0.3202 m.glm<-glm(mark~x+poly(elevation,2)+bs(distance,degree=1,knots=c(16.13,24)) +bs(y,degree=1,knots=c(-0.4357,-0.3202

Dear friends, Anybody has ever met the problem to add a legend to a figure generated by image()? I have three variables,x,y and z. x and y are the coordinates, and z is the third values. we can use image(x, y, z,...) to generate a figure according to the z-values, but the problem is the figure legend. How can the legend be added to a figure generated by image()? Note that filled.contour() can

Dear all, Some functions like 'ROC(Epi)' can be used to perform ROC analyssi, but it needs us to specify the fitting model in the argument. Now i have got the predicted p-values (0,1) for the 0/1 response variable using some other approach, see the following example dataset: id mark predict.pvalue 1 1 0.927 2 0 0.928 3 1 0.928 ..................

Dear friends, I need the get the 2.5% and 97.5% quantile from each row of a matrix, how should i get it? BTW, i can get the min/max value from each row of a matrix, using the following programs, is there an easy function to do it? simmin<-matrix(NA,nrow=47,ncol=1) for (i in 1:47) { simmin[i,]<-min(datas[i,]) } Thanks for your help. -- With Kind Regards, oooO:::::::::

Dear R friends, When fitting GLMs in R, we may need to specify the variance function to do our analysis. I had thought it's the mean value, but it seems not. Could anybody expain the correct meaning of *mu* in the variance function of GLMs? The following content is from the R-hlep. variance for all families other than quasi, the variance function is determined by the family. The quasi

Dear friends, Now, when i use the argument return(x=x,y=y,prob=prob) , R displays the waring message: Warning message: The return value for multiple variables wasn't used in: return(x = x, y = gy, prob = prob) I used the methods of "help.search("return")" and "?return" to get some help, but didn't find info on it. Anybody knows how it should be used

Dear all, I am thinking to fit a multilevel dataset with R. I have found several possible packages for my task, such as glmmPQL(MASS),glmm(repeated),glmer(lme4), et al. I am a little confused by these functions. Could anybody tell me which function/package is the correct one to analyse my dataset? My dataset is as follows: the response variable P is binary variable (the subject is a patient

Dear all, I run the GAMs (generalized additive models) in gam(mgcv) using the following codes. m.gam <-gam(mark~s(x)+s(y)+s(lstday2004)+s(ndvi2004)+s(slope)+s(elevation)+disbinary,family=binomial(logit),data=point) And two repeated warnings appeared. Warnings$B!'(B 1: In gam.fit(G, family = G$family, control = control, gamma = gamma, ... : Algorithm did not converge 2: In gam.fit(G,

Dear friends, My dataset have many zeros, so i must use fisher exact test . Unfortunately, the fisher.test(stats) function fail to do it. Anybody knows how to do the fisher exact test with many zeros in the dataset? My dataset is: a<-matrix(c(0,1,0,0,0,0,1,0,1,0,0,0,0,1,0,1,1,0,2,1,5,1,1,6,4,4,1,17,2,8,5,7,1,1,24,3,6,1,1,3,2,16,7,4,0,2,4,0,17,0,1,0,0,0,1,2),nrow=8,byrow=TRUE) data.frame(a)