Displaying 20 results from an estimated 88 matches for "indeped".
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indeed
2013 Mar 21
4
easy way of paste
Hello,
Is there a better way to use paste such as:
a = paste(colnames(list.indep)[1],colnames(list.indep)[2],colnames(list.indep)[3],colnames(list.indep)[4],colnames(list.indep)[5],sep="+")
> a
[1] "aa+dummy1+dummy2+bb+cc"
I tried
a = paste(colnames(list.indep)[1:5],sep="+")
> a
[1] "aa" "dummy1" "dummy2"
2008 May 22
1
How to account for autoregressive terms?
Hi,
how to estimate a the following model in R:
y(t)=beta0+beta1*x1(t)+beta2*x2(t)+...+beta5*x5(t)+beta6*y(t-1)+beta7*y(t-2)+beta8*y(t-3)
1) using "lm" :
dates <- as.Date(data.df[,1])
selection<-which(dates>=as.Date("1986-1-1") & dates<=as.Date("2007-12-31"))
dep <- ts(data.df[selection,c("dep")])
indep.ret1
2012 Sep 29
1
Unexpected behavior with weights in binomial glm()
Hi useRs,
I'm experiencing something quite weird with glm() and weights, and
maybe someone can explain what I'm doing wrong. I have a dataset
where each row represents a single case, and I run
glm(...,family="binomial") and get my coefficients. However, some of
my cases have the exact same values for predictor variables, so I
should be able to aggregate up my data frame and
2005 Jun 17
0
another aov results interpretation question
I commend you to (a) the recent article by Doug Bates on "Fitting
nonlinear mixed models in R" pp. 27-30 in the latest issue of "R News"
available from "www.r-project.org" -> Newsletter and (b) Doug's book
with Pinheiro (2000) Mixed-Effects Models in S and S-PLUS (Springer). I
suggest you try the same analysis using in "lmer", library(lme4), and
2012 Jan 15
1
Need help interpreting the logit regression function
Hello R community,
I have a question about the logistic regression function.
Specifically, when the predictor variable has not just 0's and 1's,
but also fractional values (between zero and one). I get a warning
when I use the "glm(formula = ... , family = binomial(link =
"logit"))" which says:
"In eval(expr, envir, enclos) : non-integer #successes in a binomial
2009 Feb 03
1
How to show variables used in lm function call?
Hello R users,
I am new to R and am wondering if anyone can help me out
with the following issue: I wrote a function to build ts models using
different inputs, but when R displays the call for a model, I cannot tell
which variables
it is using because it shows the arguments instead of the real variables
passed to the function.
(e.g
Call:
lm(formula = dyn(dep ~ lag(dep, -1) + indep)) --->
2010 Mar 16
3
function arguments: name of an object vs. call producing the object?
In a function, say foo.glm for glm objects I want to use the name of the
object as a label for some output,
but *only* if a glm object was passed as an argument, not a call to
glm() producing that object.
How can I distinguish these two cases?
For example, I can use the following to get the name of the argument:
foo.glm <- function(object) {
oname <- as.character(sys.call())[2]
2009 Jun 21
2
Help on qpcR package
I am using R on a Windows XP professional platform.
The following code is part of a bigger one
CODE
press=function(y,x){
library(qpcR)
models.press=numeric(0)
cat("\n")
dep=y
print(dep)
indep=log(x)
print(indep)
yfit=dep-PRESS(lm(dep~indep))[[2]]
cat("\n yfit\n")
print(yfit)
yfit.orig=yfit
presid=y-yfit.orig
press=sum(presid^2)
2013 Mar 22
0
predict.Arima error "'xreg' and 'newxreg' have different numbers of columns"
Hello all,
I use arima to fit the model with
fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE)
and would like to use predict() to forecast:
chn.forecast <- rep(0,times=num.record)
chn.forecast[1] <- y[1]
for (j in 2:num.record){
indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the
2002 Mar 15
1
calibration/inverse regression?
I wonder if anyone out there has written a routine to solve the simple
linear calibration problem?
- fit regression of y vs x
- estimate the value x0 (with 95% CI) that gives y0
Thanks for any help.
Bill
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r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info",
2005 Mar 30
2
Step error
Could anyone tell me what am I doing wrong?
> pro<-function(indep,dep){
+ d<-data.frame(indep)
+ form<-formula(lm(dep~.,data=d))
+
forward<-step(lm(dep~X1,data=d),scope=form,trace=0,direction='f')
+ return(forward)
+ }
> pro(m,q)
Error in inherits(x, "data.frame") : Object "d" not
found
Where q is a vector with the dependent variable's
2010 Mar 11
0
Different results for different order of factor levels?
Dear R community,
I am a newbie to R and I am using lme() to analyzed a two way repeated
measures ANCOVA on some data I have gathered. In producing some
graphs based on the fixed effects I noticed that I get vary different
results depending on how I order my levels in my factor statement (see
code below). Now, I have read that different models treat data from
the factor class
2009 Feb 07
3
Output results to a single postscript document
Hello R users,
I have been trying to output all my results (text, plots, etc) into the same
postscript file as
one document, but have been unable to...Can anyone help me improve my code
below so that I can
accomplish this? Currently I have to output them separately then piece them
back together into
one document..
Thanks in Advance for any help!
options (scipen=999, digits=7)
2008 Sep 03
1
test if all predictors in a glm object are factors
I'm trying to develop some graphic methods for glm objects, but they
only apply for models
where all predictors are discrete factors. How can I test for this in a
function, given the
glm model object?
That is, I want something that will serve as an equivalent of
is.discrete.glm() in the following
context:
myplot.glm <-
function(model, ...) {
if (!inherits(model,"glm"))
2008 Apr 09
0
energy 1.1-0 with dcov
Dear R-users,
An updated version of the energy package, energy 1.1-0, is now available on
CRAN.
This version has merged the dcov package (previously available from my
personal web page) into energy.
New functions include:
dcov (distance covariance)
dcor (distance correlation)
DCOR (four statistics)
dcov.test (distance covariance test of multivariate independence)
indep.test (choice of
2008 Apr 09
0
energy 1.1-0 with dcov
Dear R-users,
An updated version of the energy package, energy 1.1-0, is now available on
CRAN.
This version has merged the dcov package (previously available from my
personal web page) into energy.
New functions include:
dcov (distance covariance)
dcor (distance correlation)
DCOR (four statistics)
dcov.test (distance covariance test of multivariate independence)
indep.test (choice of
2004 Oct 07
5
'with' usage question
Default arguments are evaluated in the function frame, not in the calling
environment (nor in the same place as explicit arguments).
> Which to me reads that a with statement as above is equivalent to
>
> > attach(data) ; aov.SS1(y=Obs) ; detach(data)
>
> Or is that just wishful thinking??
The latter.
On Thu, 7 Oct 2004, RenE J.V. Bertin wrote:
> Hello,
>
>
2009 Nov 04
1
variable selectin---reduce the numbers of initial variable
hello,
my problem is like this: now after processing the varibles, the remaining
160 varibles(independent) and a dependent y. when I used PLS method, with 10
components, the good r2 can be obtained. but I donot know how can I express
my equation with the less varibles and the y. It is better to use less
indepent varibles. that is how can I select my indepent varibles. Maybe
GA is good
2000 Mar 31
1
R: one bananna aov() question
Hello world,
I'm trying to do an
anova on data in data.set, dependent variable is a column
named "dep.var", grouping variable is in a column called "indep.var", and
is.factor(indep.var) is TRUE...
why can't I just do aov(dep.var ~ indep.var, data = data.set)?
What have I done to deserve this?! What gives? Am I missing something
totlly obvious?
R-base-1.0.0-1,
2011 Jul 06
2
wgcna
Hi,
I'm running a tutorial ("Meta-analyses of data from two (or more) microarray data sets"), which use wgcna package. I have an error in the function modulePreservation (it is below).
I'm using R2.13
Can you help me? Do you know, what is happens?
Thanks
Raquel
multiExpr = list(A = list(data=t(badea)),B = list(data=t(mayo)))
# two independent datasets (dim = 13447 x 36)
mp =