similar to: Subset command and the : operator

I am using the following command to replace all the missing values and assorted typos in a dataframe with NA: mydata[mydata>80]=NA The problem is that the first column contains values which should be more than 80, so really I want to do it just for mydata[,2:length(mydata)] I can't seem to re-write the code to fit: mydata[,2:length(mydata)>80]=NA # no error message, but doesn't

Hello- Sorry, this is a bit of a noob question, but I can't seem to progress it any further. I have two dataframes which contain a series of strings which exactly match. The problem is one has more rows than the other (more cases have been added) and they have been sorted so that they are not in the same order. The smaller dataframe, though, contains in another column which has codes

Hello- I have rather a messy SPSS file which I have imported to R, I've dput'd some of the columns at the end of this message. I wish to get rid of all the labels and have numeric values using as.numeric. The funny thing is it works like this: as.numeric(mydata[,2]) # generates correct numbers however, if I pass the whole dataframe at once like this: apply(mydata, 1:2, function(x)

Hi Ruser As so usual I'm trying to replicate some SAS code. I wold like to know if there is a wildcard operators, as " : " in SAS, in R? When running: lm(y ~ x1 + x2 + x3 + x4 + x5 + x6 .... x9860, data=mydata) I would like to be able to get around it by just writing something like this: lm(y ~ x1:x9860, data=mydata) Anyone? Sorry for no including a working example, but I

Hi All, I'm using the subset function to select a list of variables, some of which are contiguous in the data frame, and others of which are not. It works fine when I use the form: subset(mydata,select=c(x1,x3:x5,x7) ) In reality, my list is far more complex. So I would like to store it in a variable to substitute in for c(x1,x3:x5,x7) but cannot get it to work. That use of the c function

hi I am trying to write a function around a glm or similar function, in which I can pass the subsetting constraint as an argument to the function, but I am having trouble. the following commands (if I wanted SEX==0 to be my subset) in the global environment work fine: subexpr <- expression(SEX==0) subtest <- with(mydata, eval(subexpr)) test.glm <- glm(y~x1+x2, data=mydata,

Hi everyone, Let me have a dataframe named ?mydata? and created as below, *> n=c(5,5,5,5) #number of trils > x1=c(2,3,1,3) ) #number of successes > x2=c(5,5,5,5) #number of successes > x3=c(0,0,0,0) #number of successes > x4=c(5,0,5,0) #number of successes > mydata=data.frame(n,x1,x2,x3,x4) > mydata* n x1 x2 x3 x4 1 5 2 5 0 5 2 5 3 5 0 0 3 5 1 5 0 5 4 5 3 5 0

Hi, I'm using a loop to evaluate several models by taking adjacent variables from my dataframe. When i try to get predictions for new values, i get an error message about a missing variable in my new dataframe. Below is an example adapted from ?gam in mgcv package library(mgcv) set.seed(0) n<-400 sig<-2 x0 <- runif(n, 0, 1) x1 <- runif(n, 0, 1) x2 <- runif(n, 0, 1) x3 <-

Dear R Friends , I want to name my variables( more than 2 variables in a single plot) within a plot to distinct them from each other, but I cann't. How it is possible? I don't mean x and y axis using xlab or ylab. At the below , it follows some lines, only as an example that you could try please, if it is possible. I really thanks for your attention. Amir library(graphics) y<-

Dear all, for a cross-validation I have to use predict.glmmPQL() , where the formula of the corresponding glmmPQL call is not given explicitly, but constructed using as.formula. However, this does not work as expected: x1<-rnorm(100); x2<-rbinom(100,3,0.5); y<-rpois(100,2) mydata<-data.frame(x1,x2,y) library(MASS) # works as expected model1<-glmmPQL(y~x1, ~1 | factor(x2),

Dear all, mydata<-data.frame(x1=c(1,4,6),x2=c(3,1,2),x3=c(2,1,3)) cor(mydata) x1 x2 x3 x1 1.0000000 -0.5960396 0.3973597 x2 -0.5960396 1.0000000 0.5000000 x3 0.3973597 0.5000000 1.0000000 I wonder if it is possible to fill only lower triangle of this correlation matrix? Using 'dist' doesn't seem to be useful as it doesnt allow to convert this table

Hi there I want to pass arguments (i.e. the response variable and the subset argument) in a self-made function to glm. Here is one way I can do this: f.myglm <- function(y,subfact,subval) { glm(d.mydata[,y]~d.mydata[,'x1'],family=binomial,subset=d.mydata[,subfact]==subval) } > str(d.mydata) `data.frame': 15806 obs. of 3 variables: $ y : Factor w/ 2 levels

Dear experts, I have a few quick questions related to GLMs: 1) Suppose my response is of the type Yes/No, How can I control which response I'm modelling? 2) How can I perform Type III tests? Is it with -> drop1(mymodel, test="Chisq") ? 3) I have a numerical variable which I converted to an ordered factor as shown below, but in the summary results of the logistic regression I

Hello With due respect, have a nice time. I would like to ask some command in R. It is regarding variable selection in linear regression. In R, there is one rebuild function called "step" which selecting variables according to AIC. let say i have data [y, x1,x2,x3,x4] we start with y~b0 i compute the partial F test and choose the variable with maximum partial F to enter the

Hi R users I have serveral binary variables (e.g., X1, X2, X3, X4, X5, X,6, and X7) and one continuous variable (e.g., Y1). I combined these variables using data.frame() mydata <- data.frame(X1,X2,X3,X4,X5,X6,X7,Y1) after that, I sorted this data.frame rank.by.Y1<-order(mydata[,8]) sorted.mydata<-mydata[rank.by.Y1,] after that, I replaced Y1's values with values ranging from 1

Hi: I'd like to get the objects corresponding to the elements in a formula, from a data frame. For example, suppose I would like to make a function call, such as follows: myfunc(formula="y ~ x1 + x2 + log(x3)" , data=mydata) This function will get the vector objects y, x1, x2, and log(x3) from the data frame "mydata" to form the design matrix and then perform a

How can I have both printout and saved results at the same time. The subroutine first return "out" and the printout gets printed, but not saved. I then run the "invisible" line. Results got saved and accessible but no printout. How can I have both printout and also have the results saved? Thank you! > dstat4 <- function(data,digits=3){ +?? Mean??? <-

Dear All, I have some questions about probit regressions. I saw a nice introduction at http://bit.ly/bU9xL5 and I mainly have two questions. (1) The first is almost about data manipulation. Consider the following snippet ################################################## mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/binary.csv")) names(mydata) <-

Hi,   I have the following data and I would like to delete douple names, it is almost similar to SAS PROC SORT nodupkey! Is there any function in R does this?   x1 <- rnorm(11,5,1) x2 <- runif(11,0,1) nam <-paste("A", c(1:4,4,5:9,9), sep=".") mydata <- data.frame(x1,x2) crownames(mydata) <- nam   Many thanks in advance, Amor [[alternative HTML version

Thankyou for your help with subsetting within a function. I have now tried to apply the same theory in the framework of an lme as follows: fit1.lme <- eval(substitute(lme(fixed=fixed, data=dataframe, random=random, correlation=corCAR1(form= corr), na.action=na.omit, subset=subset),list(subset=subs))) but I get the following error: Error in switch(mode(object), name = , numeric = , call =