Displaying 20 results from an estimated 11000 matches similar to: "AR(1) with NLME"
2005 Oct 12
3
Calibrating both RX and TX gain?
Hello!
I'm having an echo problem with a TDM card. The TDM card is being fed by
a channel bank just 12 or so feet away. When you put an analog handset on
the line, both the RX and TX volume seem to be just fine. However, when I
use the TDM card, I have to have an rxgain of 13.5, and even then, the
audio is relatively quiet. I'm also getting echo on these lines, so I
have turned
2007 Mar 13
1
AR(1) and gls
Hi there,
I am using gls from the nlme library to fit an AR(1) regression model.
I am wondering if (and how) I can separate the auto-correlated and random
components of the residuals? Id like to be able to plot the fitted values +
the autocorrelated error (i.e. phi * resid(t-1)), to compare with the
observed values.
I am also wondering how I might go about calculating confidence (or
2009 May 05
2
calibration plot
Hi,
I have a binary variable and corresponding predicted probability (using
logistic regression on some explanatoey variables);
I want to check that the model is well-calibrated using a calibration plot.
how can I have the calibration plot for my data?
thanks.
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2004 Mar 09
2
corARMA and ACF in nlme
Hi R-sters,
Just wondering what I might be doing wrong. I'm trying to fit a multiple
linear regression model, and being ever mindful about the possibilities of
autocorrelation in the errors (it's a time series), the errors appear to
follow an AR1 process (ar(ts(glsfit$residuals)) selected order 1). So,
when I go back and try to do the simultaneous regression and error fit with
gls,
2010 Apr 17
2
interpreting acf plot
Hello,
I am attending a course in Computational Statistics at ETH and in one of the assignments I am asked to prove that a time series is not autocorrelated using the R function "acf".
I tried out the acf function with the given data, according to what I found here: http://landshape.org/enm/options-for-acf-in-r/ this test data does not look IID but rather shows some trends so how can I
2011 Sep 01
1
How to retrieve bias-corrected probability from calibrate.rms
Dear R users:
In Prof. Harrell's library rms, calibrate.rms plot the Bias-corrected
Probability and Apparent Probability.
The latter one can be retrieved from class calibrate.default. But how to
retrieve the former one.
BW
*Yao Zhu*
*Department of Urology
Fudan University Shanghai Cancer Center
Shanghai, China*
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2008 May 15
2
How to remove autocorrelation from a time series?
Dear R users,
someone knows how to remove auto-correlation from a frequencies time series?
I've tried by differencing (lag 1) the cumulative series (in order to have only positive numbers) , but I can't remove all auto-correlation.
If it's useful I can send my db.
x <- # autocorrelated series
new1<-cumsum(x)
new2<-diff(new1,lag=1,differences = 1)
acf(new2) #
2012 May 30
3
alternative generator for normal distributed variables
Hello,
currently I'm working on a model based on Monte-Carlo-Simulations.
I observed that a generated normal distributed times series using
rnorm(100,mean=0,sd=1)
is far away from being not autocorrelated.
Is there any other gerenator implemented in R, which might solve my problem?
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2010 Mar 16
4
clasificacion support vector machines (package e1071)
Hola a todos,
Estoy iniciandome en R y la verdad es que aun estoy muy muy verde....
Estoy
intentando clasificar unos datos con support vector machines, pero me
da fallo al usar la funcion predict. El código que uso es el siguiente:
calibrate<-read.table("calibration.txt", header=TRUE)
calibrate$calibration<-as.factor(calibrate$calibration)
2009 Jan 11
1
calibrate function
Hi all,
I have a question on the package « survey”
I have some difficulties to use the function ‘calibrate’. Although it works
well with one single factor variable, I cannot use it for 2 and get the
message
“Erreur dans regcalibrate.survey.design2(design, formula, population,
aggregate.stage = aggregate.stage, : Population and sample totals are not
the same length.”
Here is the format
2011 Jun 08
1
Autocorrelation in R
Hi,
I am trying to learn time series, and I am attending a colleague's
course on Econometrics. However, he uses e-views, and I use R. I am
trying to reproduce his examples in R, but I am having problems
specifying a AR(1) model. Would anyone help me with my code?
Thanks in advance!
Reproducible code follows:
download.file("https://sites.google.com/a/proxima.adm.br/main/ex_32.csv
2010 Mar 18
2
aumentar tamaño de memoria a mas de 4Gb
Hola de nuevo,
Esta es la información de mi sesion:
R version 2.10.1 (2009-12-14)
i386-pc-mingw32
locale:
[1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252
[3] LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C
[5] LC_TIME=Spanish_Spain.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
Lo que yo prentendo es
2011 Nov 28
1
detecting autocorrelation structure in panel data
Hello,
I'm a newby in R. I have created a data.frame holding panel data, with
the following columns: "id","time","y", say:
periods = 100
numcases = 100
df = data.frame(
id = rep(1:numcases,periods),
time = rep(1:periods, each = numcases)
)
df = transform(df,y=c(rnorm(numcases*periods)+id)
I want to check whether "y" is autocorrelated. I came across
2010 Feb 12
1
nlme w/no groups and spatially correlated residuals
Hi,
I would like to specify a spherical correlation structure for spatially
autocorrelated residuals in a model based upon the logistic function of a
response that is a proportion (0 to 1) (so usual binary logistic regression
is not an option). There is no need for a g-side random effect with
grouping in this model. Am I correct that nlme requires this (meaning a
correlated error structure only
2007 Oct 27
1
[non-statistics question]methodological problem
Good afternoon!
As mentioned in the subject, my question regards more the methodological part that accompanies survey design and the statistical part that is involved.
So, I have the following data:
a<-data.frame (id_hh=c(1:5), strata=c(1,1,2,2,1), Nhstrata=c(100,100,200,200,100), Nrmemb=c(2,4,2,5,4))
a$ocmemb1<-c("wk","jl","st","jl","st")
2009 Aug 13
1
R code to reproduce (while studying) Bates & Watts 1988
Hi R users,
I'm here trying to understand correlated residuals in nonlinear estimation.
I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988),
/Nonlinear regression analysis and its applications/, Wiley, NY. pages
92-94, trying to reproduce the figures and to find out the code in R to
perform the necessary calculations.
I also consulted Pinheiro and Bates, but without
2010 Aug 13
1
val.prob in the Design package - Calibrated Brier Score
Hello,
I am using the val.prob function in the Design package. I understand how
the Brier quadratic error score is calculated, but I do not know how the
Brier score computed on the calibrated rather than raw predicted
probabilities (B cal) is calculated. My question is: how are the calibrated
probabilities calculated? Any explanation of this, or references to
explanations of this, would be
2005 Apr 11
0
correlation range estimates with nlme::gls
I'm trying to do a simple (?) analysis of a 1D spatial data set,
allowing for spatial autocorrelation. (Actually, I'm comparing expected
vs. observed for a spatial model of a 1D spatial data set.) I'm using
models like
gls(obs~exp,correlation=corExp(form=~pos),data=data)
or
gls(obs~exp,correlation=corLin(form=~pos),data=data)
This form is supposed to fit a linear model of
2008 Dec 18
4
autologistic modelling in R
Hi,
I have spatially autocorrelated data (with a binary response variable and
continuous predictor variables). I believe I need to do an autologistic
model, does anyone know a method for doing this in R?
Many thanks
C Bell
2011 Sep 06
1
calibrate.cph plots
Hi!
How can I exclude the legends from calibration plots
generated by calibrate.cph
regards,
Salvo
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