Displaying 13 results from an estimated 13 matches for "resvars".
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resvar
2015 Jan 14
2
R CMD check: "..." used in a situation where it does not exist
...(unstable)
(2015-01-13 r67453) gives me the following NOTE:
cbind.fsets: possible error in list(...): ... used in a situation
where it does not exist
The file that causes this note contains:
cbind.fsets <- function(..., deparse.level = 1) {
dots <- list(...)
res <- NULL
resVars <- NULL
resSpecs <- NULL
for (i in seq_along(dots)) {
arg <- dots[[i]]
argName <- names(dots)[i]
if (!is.null(arg)) {
if (!is.fsets(arg)) {
stop("Function 'cbind.fsets' cannot bind arguments
that are not valid ...
2015 Jan 14
0
R CMD check: "..." used in a situation where it does not exist
...t;
>
> cbind.fsets: possible error in list(...): ... used in a situation
> where it does not exist
>
>
> The file that causes this note contains:
>
>
> cbind.fsets <- function(..., deparse.level = 1) {
> dots <- list(...)
>
> res <- NULL
> resVars <- NULL
> resSpecs <- NULL
>
> for (i in seq_along(dots)) {
> arg <- dots[[i]]
> argName <- names(dots)[i]
>
> if (!is.null(arg)) {
> if (!is.fsets(arg)) {
> stop("Function 'cbind.fsets'...
2004 Jan 12
1
question about how summary.lm works
Hi,
While exploring how summary.lm generated its output I came across a section
that left me puzzled.
at around line 57
R <- chol2inv(Qr$qr[p1, p1, drop = FALSE])
se <- sqrt(diag(R) * resvar)
I'm hoping somebody could explain the logic of these to steps or
alternatively point me in the direction of a text that will explain these
steps.
In particular I'm puzzled
2005 Mar 03
2
regression on a matrix
Hi -
I am doing a monte carlo experiment that requires to do a linear
regression of a matrix of vectors of dependent variables on a fixed
set of covariates (one regression per vector). I am wondering if
anyone has any idea of how to speed up the computations in R. The code
follows:
#regression function
#Linear regression code
qreg <- function(y,x) {
X=cbind(1,x)
m<-lm.fit(y=y,x=X)
2006 Nov 24
2
low-variance warning in lmer
For block effects with small variance, lmer will sometimes
estimate the variance as being very close to zero and issue
a warning. I don't have a problem with this -- I've explored
things a bit with some simulations (see below) and conclude that
this is probably inevitable when trying to incorporate
random effects with not very much data (the means and medians
of estimates are plausibly
2009 Jul 08
1
functions to calculate t-stats, etc. for lm.fit objects?
I'm running a huge number of regressions in a loop, so I tried lm.fit
for a speedup. However, I would like to be able to calculate the
t-stats for the coefficients.
Does anyone have some functions for calculating the regression summary
stats of an lm.fit object?
Thanks,
Whit
2011 Aug 01
3
formula used by R to compute the t-values in a linear regression
Hello,
I was wondering if someone knows the formula used by the function lm to compute the t-values.
I am trying to implement a linear regression myself. Assuming that I have K variables, and N observations, the formula I am using is:
For the k-th variable, t-value= b_k/sigma_k
With b_k is the coefficient for the k-th variable, and sigma_k =(t(x) x )^(-1) _kk is its standard deviation.
1998 May 29
0
aov design questions
R developers,
I have a first attempt to make an aov function. Eventually I want to
build in Error() structure, but first I am trying to get this
presentable for balanced data with only a single stratum, just using
residual error. I am following R. M. Heiberger's Computation for the
Analysis of Designed Experiments, Wiley (1989)
I a using a wrapper (aov.bal) to call the
2009 Jul 26
0
Version 0.7 of package tsDyn, nonlinear time series
Hi
Version 0.7 of package tsDyn presented at useR! 2009 is now on CRAN,
extended with several new features.
The package tsDyn is aimed at estimating nonlinear time series models
which exhibit regime specific properties. The regime switching dynamics
can either be described by smooth transition (STAR and LSTAR) or
threshold effects (SETAR). The package furthermore offers nonlinear
models
2009 Jul 26
0
Version 0.7 of package tsDyn, nonlinear time series
Hi
Version 0.7 of package tsDyn presented at useR! 2009 is now on CRAN,
extended with several new features.
The package tsDyn is aimed at estimating nonlinear time series models
which exhibit regime specific properties. The regime switching dynamics
can either be described by smooth transition (STAR and LSTAR) or
threshold effects (SETAR). The package furthermore offers nonlinear
models
2008 Feb 26
3
OLS standard errors
Hi,
the standard errors of the coefficients in two regressions that I computed
by hand and using lm() differ by about 1%. Can somebody help me to identify
the source of this difference? The coefficient estimates are the same, but
the standard errors differ.
####Simulate data
happiness=0
income=0
gender=(rep(c(0,1,1,0),25))
for(i in 1:100){
happiness[i]=1000+i+rnorm(1,0,40)
2012 Mar 25
2
avoiding for loops
I have data that looks like this:
> df1
group id
1 red A
2 red B
3 red C
4 blue D
5 blue E
6 blue F
I want a list of the groups containing vectors with the ids. I am
avoiding subset(), as it is
only recommended for interactive use. Here's what I have so far:
df1 <- data.frame(group=c("red", "red", "red", "blue",
2009 Jul 09
2
How to Populate List
Hi,
I'm new to R and would like to know, how one can populate the list with array data.
I'm reading a tab separated table in R. The data in the table looks something like this.
#Table Data
Comp A B C
Extracellular 103 268 535759
Nucleus 45603 47783 442744
#R code
myData <- read.table("table.data",
header=T,