Displaying 20 results from an estimated 2000 matches similar to: "strength of seasonal component"
2012 Mar 21
3
how calculate seasonal component & cyclic component of time series?
i am new to time series,whatever i know up till now,from that
i have uploaded time series file & what to build arma model,but for that i
want p & q values(orders)
tell me how to calculate best p & q values to find best AIC values for model
i am doing but giving error
>bhavar<-read.table(file.choose()) #taking time series file
> decompose(bhavar$V1)
Error in
2013 Feb 22
2
Model selection in nonstationary VAR
Folks,
Is there any implementation available in R for the simultaneous selection of lag order and rank of a nonstationary VAR as described in Chao & Phillips (1999): Model selection in partially nonstationary vector autoregressive processes with reduced rank structure, J. Econ. (91).
Or any other systematic procedure for the consistent selection of lag order and cointegration rank?
I
2012 Dec 23
3
Spammer radhi
This happened two or three weeks ago and it's happening again.
Spammers are using Nabble to attack R-Help. The psts are signed radhi
and the posts' titles are taken from previous posts and therefore seem
authentic but all messages end with "click here". I suggest you don't.
And don't rply to this "radhi"
And again on a weekend.
Rui Barradas
2012 Mar 07
1
VECM simulation
Dear members,
I estimated a vector error correction model (VECM) using the "ca.jo"
function in package "urca". I need to simulate the estimated model using R.
I am aware how to simulate a VAR(p) model. Since the VECM is
in difference form, I can't modify the VAR simulation codes to VECM. May
one help me in this regard please?
Thanks
Mamush
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2011 Jul 13
3
Colors in R
HI everyone,
I''m trying to assign colors to multiple lines in a graph. Problem is I don''t want to type in as many colors as there are lines....is there a way around this? In brief, I''m plotting the logratio for up to 60 samples and want a different color for each sample. Here is the code I''m using now..
Any help is greatly appreciated..
Best
LT
data <-
2011 Jun 07
2
About DCC-garch model...
Hi, everyone,
I currently run into a problem about DCC-Garch model. I use the package
cc-garch and the function dcc.estimation. One of the output of this function
is DCC matrix, which shows conditional correlation matrix at every time
period you gives. However, I cannot figue out how the function calculate the
conditional correlation matrix at the first time period, since there is no
data to be
2011 Jun 28
2
Running R from windows command prompt
1. I have a R program in a file say "functions.R".
I load the "functions.R" file the R using source("function.R") and then call
functionsf1(), f2() etc. which are declared and defined within "function.R"
file.
I also need to load a couple of R libraries using library() before I can
use f1(), f2() etc.
My question is can I acheive all this (i.e. calling
2003 Oct 02
4
using a string as the formula in rlm
Hi,
I am trying to build a series of rlm models. I have my data frame and
the models will be built using various coulmns of the data frame.
Thus a series of models would be
m1 <- rlm(V1 ~ V2 + V3 + V4, data)
m2 <- rlm(V1 ~ V2 + V5 + V7, data)
m3 <- rlm(V1 ~ V2 + V8 + V9, data)
I would like to automate this. Is it possible to use a string in place
of the formula?
I tried doing:
fmla
2011 Mar 14
1
discrepancy between lm and MASS:rlm
Dear R-devel,
There seems to be a discrepancy in the order in which lm and rlm evaluate their arguments. This causes rlm to sometimes produce an error where lm is just fine.
Here is a little script that illustrate the issue:
> library(MASS)
> ## create data
> n <- 100
> dat <- data.frame(x=rep(c(-1,0,1), n), y=rnorm(3*n))
>
> ## call lm, works fine
> summary(lm(y ~
2005 Mar 24
1
Robust multivariate regression with rlm
Dear Group,
I am having trouble with using rlm on multivariate data sets. When I
call rlm I get
Error in lm.wfit(x, y, w, method = "qr") :
incompatible dimensions
lm on the same data sets seem to work well (see code example). Am I
doing something wrong?
I have already browsed through the forums and google but could not find
any related discussions.
I use Windows XP and R
2010 Nov 08
1
Add values of rlm coefficients to xyplot
Hello,
I have a simple xyplot with rlm lines.
I would like to add the a and b coefficients (y=ax+b) of the rlm calculation
in each panel.
I know I can do it 'outside' the xyplot command but I would like to do all
at the same time.
I found some posts with the same question, but no answer.
Is it impossible ?
Thanks in advance for your help.
Ptit Bleu.
x11(15,12)
xyplot(df1$col2 ~
2009 Dec 03
2
Avoiding singular fits in rlm
I keep coming back to this problem of singular fits in rlm (MASS library),
but cannot figure out a good solution.
I am fitting a linear model with a factor variable, like
lm( Y ~ factorVar)
and this works fine. lm knows to construct the contrast matrix the way I
would expect, which puts the first factor as the baseline level.
But when I try
rlm( Y ~ factorVar)
I get the message "'x'
2004 Oct 11
3
split and rlm
Hello, I'm trying to do a little rlm of some data that looks like this:
UNIT COHORT perdo adjodds
1010 96 0.39890 1.06894
1010 97 0.48113 1.57500
1010 98 0.36328 1.21498
1010 99 0.44391 1.38608
It works fine like this: rlm(perdo ~ COHORT, psi=psisquare)
But the problem is that I have about 100 UNITs, and I want to do a
2004 Apr 07
4
Problems with rlm
Dear all,
When calling rlm with the following data, I get an error. (R v.1.8.1,
WinXP Pro 2002 with service pack 1.)
> d <- na.omit(data.frame(CPRATIO, HEIGHTZ, FAMILYID))
> c <- tapply(d$CPRATIO, d$FAMILYID, mean)
> h <- tapply(d$HEIGHTZ, d$FAMILYID, mean)
> c
1 2 3 6 7 9 10
11
6.000000 2.500000 3.250000
2004 Jun 11
1
comparing regression slopes
Dear List,
I used rlm to calculate two regression models for two data sets (rlm
due to two outlying values in one of the data sets). Now I want to
compare the two regression slopes. I came across some R-code of Spencer
Graves in reply to a similar problem:
http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html
The code was:
> df1 <- data.frame(x=1:10, y=1:10+rnorm(10))
2012 Jul 06
1
How to do goodness-of-fit diagnosis and model checking for rlm in R?
Hi all,
I am reading the MASS book but it doesn't give examples about the diagnosis
and model checking for rlm...
My data is highly non-Gaussian so I am using rlm instead of lm.
My questions are:
0. Are goodness-of-fit and model-checking using rlm completely the same as
usual regression?
1.
Please give me some pointers about how to do goodness-of-fit and
residual diagnosis for
2008 May 14
1
rlm and lmrob error messages
Hello all,
I'm using R2.7.0 (on Windows 2000) and I'm trying do run a robust
regression on following model structure:
model = "Y ~ x1*x2 / (x3 + x4 + x5 +x6)"
where x1 and x2 are both factors (either 1 or 0) and x3.....x6 are numeric.
The error code I get when running rlm(as.formula(model), data=daymean) is:
error in rlm.default(x, y, weights, method = method, wt.method =
2007 Nov 29
1
relative importance of predictors
Hei Group,
I want to compare the relative importance of predictors in a multiple
linear regression y~a+bx1+cx2...
However, bptest indicates heteroskedasticity of my model. I therefore
perform a robust regression (rlm), in combination with bootstrapping (as
outlined in J. Fox, Bootstrapping Regression Models).
Now I want to compare the relative importance of my predictors. Can I rely
on the
2008 Dec 08
1
residual standard error in rlm (MASS package)
Hi,
I would appreciate of someone could explain how the residual standard
error is computed for rlm models (MASS package). Usually, one would
expect to get the residual standard error by
> sqrt(sum((y-fitted(fm))^2)/(n-2))
where y is the response, fm a linear model with an intercept and slope
for x and n the number of observations. This does not seem to work for
rlm models and I am wondering
2005 Feb 25
1
vcov on result of rlm() yields "-- please report!" (PR#7707)
Dear r-bugs,
I looked over the FAQ. Hope I'm reporting this correctly.
I ran this on both solaris and windows. I've provided terminal snapshots
which include how R was called from the command line, and the
result of version at the R prompt.
I have attached the .r file, and the data file and the output snapshots.
Below also find everything except only a few lines of the data file.
Note