similar to: how do we sample in spatial statistics?

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 Ruser, I use abline() function to add the reference line successfully, but i can't display the values corresponding to the reference line on the x/y axis, anybody knows how to display it? *My simulated programs:* y<-rnorm(50) plot(x,y) abline(v=0.5) *#my question is how to display x=0.5 in the x axis?* Thanks in advance. -- With Kind Regards, oooO::::::::: (..):::::::::

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 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 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 friends, suppose i want to do the following caulation for 100 times, how to put the results of x , y and z into the same dataframe/dataset? x<-runif(1) y<-x+1 z<-x+y thanks in advance! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology School of Public Health Fudan University Tel:86-21-54237149 [[alternative HTML version deleted]]

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 Rusers, My question is about "recode variables". First, i'd like to say something about the idea of recoding: My dataset have three variables:type,soiltem and airtem,which means grass type, soil temperature and air temperature. As we all known, the change of air temperature is greater than soil temperature,so the values in those two different temperaturemay represent different

Dear Rusers, The default behavior in R when performing a regression model with missing values is to exclude any case that contains a missing value? How could i set the bahavior that R deal with missing values? e.g.: exclude cases listwise exclude cases pairwise replace with mean Thanks very much! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology School of Public Health Fudan

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 friends, After fitting a generalized linear models ,i hope to get the variance of alpha,variance of beta and their covariance, that is , the variance-covariance matrix/information of alpha and beta , suppose *B* is the object of GLMs, i use attributes(B) to look for the options ,but can't find it, anybody knows how to get it? > attributes(B) $names [1] "coefficients"

Dear friends, In s-plus, lm() generates the the studentized residuals automatically for us, and In R, it seems don't have the results: After i fitted lm(), i use attibutes() to see the objects and didn't find studentized residuals . How to get the the studentized residuals in lm(),have i missed something? thanks very much! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology

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 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 friends, I searched the R site and found a lot of results on general linear model and generalized linear model , and i was confused by them. Here, I only want to get some concise answers on the following questions and i'll study it by your hints: 1. Which function(package) could be used to fit the general linear model ? 2. Which function(package) could be used to fit the generalized

Dear friends, When i read the R-help , i often find the following case: e.g.:surf.gls(np, covmod, x, y, z, nx = 1000, ...) #Package Spatial: Arguments: covmod: function to evaluate covariance or correlation function * ...: parameters for 'covmod'* How should i find the further information on "*...: parameters for 'covmod'*" ? I use the ?covmod, but

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

hi,friends, we all know that moran's I index and Geary'C index can be used to test spatial autocorrelation in both the area data and point data, but i only can find something on how to calculate on the data of area, and can't find the methods to perform it on the point data, could anybody give me some information, thanks in advance! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of

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, summary() doesn't give a good ouput style,e.g.: grass soiltem airtem gheight humidity altitude diluo :38 Min. :15.90 Min. :17.70 Min. : 8.00 Min. : 0.2360 high: 43 huanghuacai:32 1st Qu.:19.32 1st Qu.:22.60 1st Qu.:40.00 1st Qu.: 0.3190 low :119 hucao :46 Median :20.20 Median :25.30 Median :60.00