Displaying 18 results from an estimated 18 matches for "estiamt".
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estiamte
2010 Feb 18
0
Chisq test for truncated count data and estiamte the expectation value
...which can test the goodness of fit of truncated count data for
the given distribution.
If you have any suggestions (packages, book, or paper), it will be really
helpful to my research.
Have a nice day.
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2003 Oct 30
0
Variance of a non-linear combination of the coefficient estiamtes
Hi,
I would like to know if anyone knows how to compute a variance of the
non-linear combination of the coefficient estimates.
Say, I get a model of
y~c+ax+bz (1)
where x and z are the independent variables, c is the constant estimate, and a
and b are the coefficient estimates.
Then, I want to know the variance of
b*c/a (2).
How am I going to get it?
In Stata, I can just use
2005 Dec 16
3
partially linear models
Hey,
I am estiamting a partially linear model y=X\beta+f(\theta) where the f(\theta) is estiamted using wavelets.
Has anyone heard of methods to test if the betas are significant or to address model fit?
Thanks for any thoughts or comments.
Elizabeth Lawson
________________________________________...
2007 Jan 16
2
ARIMA xreg and factors
...r message, but I do not seem to get estimates for all
the levels of the factor. Can/how does ARIMA handle factors in xreg?
here is some example code:
sim.ar <- arima.sim(list(ar = c(0.4, 0.4)), n = 1000)
z<- factor(rep((1:5),200))
arima(sim.ar,order=c(2,0,0),xreg=z)
I only get a single estiamte for xreg. Am I thinking about this wrong (I
expected 4).
thank you,
Spencer
[[alternative HTML version deleted]]
2011 Oct 11
1
Count model prediction
Hello ;
I am doing a regression of count data (number of award and there are some
covariates)
I have estiamted the parameters of negative binomial distribuion (lambda is
a function of covaraites, GLM model) by glm.nb function and training
dataset.
Now I want to predict the number of award (for example y=0, y=1, y=2,) or
testing dataset. I dont know how to calculate this numbers?
I would be very grateful...
2012 Feb 15
1
Parameter estimation of gamma distribution
Hi,
I am trying to estiamte parameters for gamma distribution using mle for
below data using fitdist & fitdistr functions which are from "fitdistrplus"
& "MASS"packages . I am getting errors for both functions. Can someone
please let me know how to overcome this issue??
data
y1<-
c(256656, 7...
2007 Apr 23
4
Estimates at each iteration of optim()?
I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the estimate values at each iteration.
Deepankar
2007 Jul 19
5
ridiculous slow gigabit transfer, faster with VNC
...m any win32 system to any unix
system, much slower than expected.
Using scp from the linux lapotp to solaris desktop is 10Mb/sec as
expected (laptop has 100mbit only).
Using samba to copy a 1GB file I get about 7 minutes from win32 to
opensolaris. From opensolaris to win32 the windows dialog says
estiamted time 142 mins. Using plain FTP it takes 25sec. This is very
consistent.
A twist is that if a VNC client is open from the win32 desktop to the
opensolaris box the estimated transfer time via samba from opensolaris
to win32 drops right down to about 4 min. Much better, but still
nowhere near the F...
1999 Jul 26
0
: Repeated measurements data
...of
problems:
1. Varying the initial estimates of the ARMA parameters results in
different fitted models and, in particular, the values of minus
log-likelihood. How can I choose a "best" model? Some fitted
models return NaN for some of the se's and/or correlations of the
parameter estiamtes so presumably these can be ruled out.
2. I am not sure how I specify that I want random effects in the
model and nor the nature of these (eg random intercept or random
intercept and slope, etc).
Any help would be greatly appreciated.
Peter
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....
2007 Oct 04
0
SETAR and nonlinear model estimation
...g a research paper that requires the estimation of a thereshold model. I have gone through the reference manual for the pacjage "tsdyn" and i am failing to see how the the threshold models provided by R can estimate a model in which the other control variables exist or are included in the estiamtion of the model.
Any help provided will be greatly appreciated
Andrew Phiri
Post-gratuate student at the North West University (NWU), South Africa
---------------------------------
Luggage? GPS? Comic books?
[[alternative HTML version deleted]]
2004 Nov 18
0
implementing a "loop" using by(x,x$factor,FUN)
...of looping and would
ideally like to write it so that it avoid the use of "for" loop ... however I'm
having some trouble.
Very briefly, the basic idea is to implement a binary partitioning algorithm to
determine the optimal cutpoint based on deviance measures obtained from
likelihood estiamtes. This is in the geo-spatial context so I'm actually using
the geoRglm package to obtain this likelihood fit. I initially use the "variog"
function to help specify the initial parameter values passed to "likfit" to
ensure convergence.
Although not the most elegant soluti...
2003 Oct 30
0
Variance of a non-linear combination of the coefficient e stiamtes
...Statistics :
original bias std. error
t1* 1.391884 0.2708119 16.32276
>
bob
-----Original Message-----
From: umeno [mailto:umeno@students.uiuc.edu]
Sent: Thursday, October 30, 2003 1:19 PM
To: R-Help <r-help
Subject: [R] Variance of a non-linear combination of the coefficient
estiamtes
Hi,
I would like to know if anyone knows how to compute a variance of the
non-linear combination of the coefficient estimates.
Say, I get a model of
y~c+ax+bz (1)
where x and z are the independent variables, c is the constant estimate, and
a
and b are the coefficient estimates.
Then, I wan...
2011 Apr 19
1
Prediction interval with GAM?
Hello,
Is it possible to estimate prediction interval using GAM? I looked through
?gam, ?predict.gam etc and the mgcv.pdf Simon Wood. I found it can
calculate confidence interval but not clear if I can get it to calculate
prediction interval. I read "Inference for GAMs is difficult and somewhat
contentious." in Kuhnert and Venable An Introduction to R, and wondering why
and if that
2007 Sep 19
3
Robust or Sandwich estimates in lmer2
Dear R-Users:
I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works in lmer2 to get the robust estimates of
2005 Jan 11
3
Kolmogorov-Smirnof test for lognormal distribution with estimated parameters
Hello all,
Would somebody be kind enough to show me how to do a KS test in R for a
lognormal distribution with ESTIMATED parameters. The R function
ks.test()says "the parameters specified must be prespecified and not
estimated from the data" Is there a way to correct this when one uses
estimated data?
Regards,
Kwabena.
--------------------------------------------
Kwabena Adusei-Poku
2000 Nov 15
2
loess documentation
Hi all,
I 've got a question about the usage of loess in the modreg package.
The documentation (loess.html) states that the smoothing window is
either set by span or enp.target. If span is used, the details section
of the docs state...
<SNIP>
DETAILS
Fitting is done locally. That is, for the fit at point x, the fit is
made using points in a neighbourhood of x, weighted by their
2000 Nov 15
2
loess documentation
Hi all,
I 've got a question about the usage of loess in the modreg package.
The documentation (loess.html) states that the smoothing window is
either set by span or enp.target. If span is used, the details section
of the docs state...
<SNIP>
DETAILS
Fitting is done locally. That is, for the fit at point x, the fit is
made using points in a neighbourhood of x, weighted by their
2010 Dec 13
2
Complicated nls formula giving singular gradient message
I'm attempting to calculate a regression in R that I normally use Prism for,
because the formula isn't pretty by any means.
Prism presents the formula (which is in the Prism equation library as
Heterologous competition with depletion, if anyone is curious) in these
segments:
KdCPM = KdnM*SpAct*Vol*1000
R=NS+1
S=(1+10^(X-LogKi))*KdCPM+Hot
a=-1*R
b=R*S+NS*Hot+BMax
c = -1*Hot*(S*MS+BMax)
Y