Displaying 6 results from an estimated 6 matches for "fitn".
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2011 Feb 15
1
Estimation of an GARCH model with conditional skewness and kurtosis
Hello,
I'm quite new to R but tried to learn as much as possible in the last
few months.
My problem is that I would like to estimate the model of Leon et al. (2005).
I have shortly summarised the most important equations in the following
pdf file:
http://hannes.fedorapeople.org/leon2005.pdf
My main question is now how could I introduce these two additional terms
into the Likelihood
2012 Apr 09
3
how to add 3d-points to bplot {rms} figure?
...<- "2dcali_red.ttt"
ux<-as.matrix(read.table(file, dec = ","))
mode(ux)<-'numeric'
vel<-ux[,1]
ang<-ux[,2]
x<-ux[,3]
y<-ux[,4]
dat<- data.frame(ang=ang, x=x,y=y)
require(rms)
ddist2 <- datadist(dat)
options(datadist="ddist2")
fitn <- lrm(ang ~ rcs(x,4) + rcs(y,4), data=dat)
predi <- Predict(fitn, x, y)
bplot(predi,lfun=wireframe, screen = list(z = -40, x = -80), drape=TRUE)*
The file 2dcali_red.ttt consists of 4 columns can be found here :
http://www.color-space.de/upload/dl/2dcali_red.ttt link
The code gives me t...
2011 Aug 21
1
Multiple R linear models into one Latex table
...ight look strange for some disciplines (I come from political science).
Thanks,
Alex
## Start script
#################################
#### R models to Latex table ####
#################################
# nice() - Multiple R linear models into one Latex table.
#
# nice(list(fit1,fit2,...,fitn)) for generic table with n models
#
# or
#
# for better tables, create objects 'model.names' and 'final.varnames', then
#
# nice(list(fit1,fit2,...,fitn), model.names, final.varnames)
nice <- function(modelos, model.names=NULL, final.varnames=NULL) {
var.names<-...
2012 Nov 28
1
Problems with nls
...ng(Laptop_sale)
Bass.Model <- Laptop_sale ~ m * ((p + q)^2/p) * (exp(-(p + q) * time)/((q /
p) * exp(-(p + q) * time) + 1)^2)
Bass.Fit <- nls(formula = Bass.Model, start = c(p = 0.03, q = 0.4, m
=max(CuSale)), trace = TRUE)
Bass.Fit
library(nlmrt)
xdata<-data.frame(Laptop_sale, time)
Bass.Fitn <- nlxb(formula = Bass.Model, start = c(p = 0.03, q = 0.4, m =
max(CuSale)), data=xdata,trace=TRUE)
Bass.Fitn
JN
> Message: 22
> Date: Tue, 27 Nov 2012 07:11:13 -0800 (PST)
> From: Yifen <yifen.chen at gmail.com>
> To: r-help at r-project.org
> Subject: Re: [R] Problem...
2012 Oct 18
3
Upper limit in nlsLM not working as expected
Dear all,
I am using the nlsLM function to fit a Lorentzian function to my experimental data.
The LM algorithm should allow to specify limits, but the upper limit appears not to work as expected in my code.
The parameter 'w', which is peak width at half maximuim always hits the upper limit if the limit is specified. I would expect the value to be in-between the upper and lower limit with
2009 Jun 23
0
Fractional Polynomials in Competing Risks setting
...ox,data=nearma,select=0.05,verbose=TRUE)
where with.Withtime is the time to treatment withdrawal, with.Wcens is
the censoring indictor for the event and all.firstint is the age at
baseline.
To look at the competing risks regression modelling when age in
untransformed, I can use the following code:
fitn<-crr(nearma$with.Withtime,censaeb,as.matrix(nearma$all.age),failcode=2,cencode=0)
where censaeb is the censoring indicator which is coded 1 for the
event of interest (time to treatment failure), 2 for the competing
risk and 0 for the censored value.
Can anyone suggest how I can effectively comb...