Displaying 20 results from an estimated 1000 matches similar to: "covariance matrix: a erro and simple mixed model question, but id not know answer sorry"
2008 Oct 01
3
"tapply versus by" in function with more than 1 arguments
Hi. I searched the list and didn't found nothing similar to this. I simplified my example like below:
#I need calculate correlation (for example) between 2 columns classified by a third one at a data.frame, like below:
#number of rows
nr = 10
#the third column is to enforce that I need correlation on two variables only
dataf =
2005 Oct 07
1
returning a modified fix()-ed dataframe
Dear all,
In order to ease the transition from SPSS to R for some of my colleagues, I am
trying to create a function which would show the variables and their labels
(if those exist), using function "label" in package Hmisc.
A toy example would be this:
my.data <- data.frame(age=c(24,35,28), gender=c("Male", "Female", "Male"))
require(Hmisc)
2010 Jul 22
1
Updating a Data Frame
Hi,
I have a global data-frame in my R script.
At some point in my script, I want to update certain columns of this
data-frame by calling in an update function.
The function looks like this:
# get events data. This populates a global event data frame in the R-script
events <- getEvents(con, eventsFilePath)
# events has columns eventid, timeStamp, isSynchronized, timeDiff; with
millions of
2009 Apr 28
1
[macosx] improving quartz & Aqua Tk behaviour outside of RGui
Hello,
On Mac OS X, certain Aqua/Quartz UI functionality requires an
application to be launched from within an app bundle, or
(alternatively) requires a Carbon application with a resource fork.
Playing with the wxWidgets distribution, I discovered that it is quite
easy and transparent to make such a Carbon app from (I guess) any
command line application. When applied to the R executable called
2009 Apr 28
1
[macosx] improving quartz & Aqua Tk behaviour outside of RGui
Hello,
On Mac OS X, certain Aqua/Quartz UI functionality requires an
application to be launched from within an app bundle, or
(alternatively) requires a Carbon application with a resource fork.
Playing with the wxWidgets distribution, I discovered that it is quite
easy and transparent to make such a Carbon app from (I guess) any
command line application. When applied to the R executable called
2011 Nov 15
2
Models with ordered and unordered factors
Hello;
I am having a problems with the interpretation of models using ordered or
unordered predictors.
I am running models in lmer but I will try to give a simplified example
data set using lm.
Both in the example and in my real data set I use a predictor variable
referring to 3 consecutive days of an experiment. It is a factor, and I
thought it would be more correct to consider it ordered.
Below
2006 Mar 07
3
glm automation
Hello,
I have two problems in automating multiple glm(s) operations.
The data file is tab delimited file with headers and two columns. like
"ABC" "EFG"
1 2
2 3
3 4
dat <- read.table("FILENAME", header=TRUE, sep="\t", na.strings="NA",
dec=".", strip.white=TRUE)
dataf <- read.table("FILENAME", header=FALSE,
2005 Jul 05
1
by (tapply) and for loop differences
I am getting a difference in results when running some analysis using by and
tapply compare to using a for loop. I've tried searching the web but had no
luck with the keywords I used.
I've attached a simple example below to illustrates my problem. I get a
difference in the mean of yvar, diff and the p-value using tapply & by
compared to a for loop. I cannot see what I am doing wrong.
2012 Aug 11
1
using eval to handle column names in function calling scatterplot graph function
I am running R version 2.15.1 in Windows XP
I am having problems with a function I'm trying to create to:
1. subset a data.frame based on function arguments (colname & parmname)
2. rename the PARMVALUE column in the data.frame based on function
argument (xvar)
3. generate charts
plotvar <- function(parentdf,colname, parmname,xvar,yvar ){
subdf <-
2004 Oct 11
2
question on function argument
dear all,
i've looked at the r-intro (chapter 10, writing your own functions)
and searched the r-help archives but am still stuck at the following.
i have a simple function, something like:
myhist<-function(yvar) {
y<-subset(myframe,yvar>1 & yvar<=150000,select=yvar)
attach(y)
hist(yvar)
}
calling it as follows:
myhist(x1)
gives the following error:
Error in
2009 Aug 12
2
Symbolic references - passing variable names into functions
Hello All,
I am trying to write a function which would operate on columns of a
dataframe specified in parameters passed to that function.
f = function(dataf, col1 = "column1", col2 = "column2") {
dataf$col1 = dataf$col2 # just as an example
}
The above, of course, does not work as intended. In some languages one
can force evaluation of a variable, and then
2007 Nov 15
1
Writing a helper function that takes in the dataframe and variable names and then does a subset and plot
Hi,
I have a large dataframe than I'm writing functions to explore, and to
reduce cut and paste I'm trying to write a function that does a subset
and then a plot.
Firstly, I can write a wrapper around a plot:
plotwithfits <- function(formula, data, xylabels=c('','')) {
xyplot(formula, data, panel =
function(x,y, ...) {
panel.xyplot(x,y,
2008 Dec 01
1
Help with lattice graphics
Hi,
I like the formatting and the appearance of lattice plots. But I have not succeeded in gettting the right format in my plots with the lattice package in one of my applications. In?the code shown below, I start by constructing a general data frame and show my attempts with the lattice package commands. After that, I use the graphics package and show the kind of plot that I want to get.
I would
2007 Jun 14
4
question about formula for lm
Dear all;
Is there any way to make this to work?:
.x<-rnorm(50,10,3)
.y<-.x+rnorm(50,0,1)
X<-data.frame(.x,.y)
colnames(X)<-c("Xvar","Yvar")
Ytext<-"Yvar"
lm(Ytext~Xvar,data=X) # doesn't run
lm(Yvar~Xvar,data=X) # does run
The main idea is to use Ytext as input in a function, so you just type
"Yvar" and the model should fit....
2011 Mar 05
2
please help ! label selected data points in huge number of data points potentially as high as 50, 000 !
Dear All
I am reposting because I my problem is real issue and I have been working on
this. I know this might be simple to those who know it ! Anyway I need help
!
Let me clear my point. I have huge number of datapoints plotted using either
base plot function or xyplot in lattice (I have preference to use lattice).
name xvar p
1 M1 1 0.107983837
2 M2 11
2010 Aug 12
2
Append to csv without header
Hi,
I am writing a function that writes to a csv file for every call.
However, for the subsequent calls, I want to append the data to the existing
csv file without appending the column names again.
I tried searching in the previous posts, but I am stuck with different
errors.
Here is what I am doing (dataF is a data-frame):-
outputFilePath <- paste(getwd(), "/",
2011 Feb 25
1
speed up process
Dear users,
I have a double for loop that does exactly what I want, but is quite
slow. It is not so much with this simplified example, but IRL it is slow.
Can anyone help me improve it?
The data and code for foo_reg() are available at the end of the email; I
preferred going directly into the problematic part.
Here is the code (I tried to simplify it but I cannot do it too much or
else it
2005 Feb 20
2
matrix operations
In R, I'm imported a data frame of 2,321,123 by 4 called "dataF".
I converted the data frame "dataF" to a matrix
dataM <- as.matrix(dataF)
Does R have an efficient routine to treat the special elements that
contain "inf" in them. For example, can you separate the rows that have
"inf" elements from the matrix into a separate matrix without
2004 Jun 24
3
The "median" function in R does not work properly.
Hi,
1.) The "median" function does not work well. Please refer to the data
below (same data is attached as txt-delimited). This is what I try to
do in R:
median ( dataf [2:9] )
I get warning: "needs numeric data"
2.) BUT if apply the median to a single vector:
median ( dataf [,2]] )
then it works:
3.) How come the "median"
2011 Mar 05
1
displaying label meeting condition (i.e. significant, i..e p value less than 005) in plot function
Dear R users,
Here is my problem:
# example data
name <- c(paste ("M", 1:1000, sep = ""))
xvar <- seq(1, 10000, 10)
set.seed(134)
p <- rnorm(1000, 0.15,0.05)
dataf <- data.frame(name,xvar, p)
plot (dataf$xvar,p)
abline(h=0.05)
# I can know which observation number is less than 0.05
which (dataf$p < 0.05)
[1] 12 20 80 269 272 338 366 368 397 403 432 453