Re: [R] Unable to pass Object Arguments to UniRoot()

2015-08-12 Thread Bazman76
yeah I found the error pls feel free to delete post!



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[R] Unable to pass Object Arguments to UniRoot()

2015-08-10 Thread Bazman76
Hi there,

I'd like to be able to pass an entire object to uniroot() as one of the
arguments. Unfortunately to recreate my precise error would be rather
involved. So I present a simplified version below:

To create a structured object let the output from the lm() function use this
simple code: 

year - c(2000 ,   2001  ,  2002  ,  2003 ,   2004)
rate - c(9.34 ,   8.50  ,  7.62  ,  6.93  ,  6.60)
fit - lm(rate ~ year)


When I try to pass this to uniroot:

OptLam-uniroot(f=LamOpt, interval=c(0.0001,120),
tol=0.0001, MLEObj=fit )

I get the following error

Error in f(lower, ...) : 
  unused argument(s) (MLEObj = list(coefficients = c(1419.207999,
-0.7049952), residuals =

This seems to be specific to uniroot I have tested my own functions and they
happily accept objects like fit. The function LamOpt is not supposed to work
with a object created by lm() I've just used lm() as a simple example so
don't worry about the results that LamOpt produces, if I can pass one object
like fit to uniroot then I assume I can pass any object.

It seems that uniroot must be expecting an object of a certain size, would
it therefore be possible to use something analogous to pointers in c/c++ and
pass the object by reference so only a pointer to the object is passed
rather than the object itself?



LamOpt-function(lambda,MLEobj){

x - c(3,6,9,12,15,18,21,24,30,36,48,60,72,84,96,108,120)

#MLEObj-kemfit
## Cross-sectional model (Nelson and Siegel)
#lambda - 0.0609
h2 - function(x){(1-exp(-lambda*x))/(lambda*x)}
h3 - function(x){((1-exp(-lambda*x))/(lambda*x)) - exp(-lambda*x)}
X=cbind(rep(1,m), h2(x), h3(x)) #obs

Z - matrix(as.list(X), ncol = 3)

MLEObj$par$Z=Z

kf_iter = MARSSkf(MLEobj)

return(-kf_iter$logLik)
}

Thanks

Baz
   




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Re: [R] Unable to pass Object Arguments to UniRoot()

2015-08-10 Thread Bazman76
Thanks Krishna!


You are correct, but even when I manually add m-17 just after x I still get
the same error?

Uniroot falls over when it tries to take in the argument MLEobj=fit, thus I
think the error is occurring before LamOpt() gets called by uniroot().

Which is why the error you mentioned didn't show up before and thus
unfortunately the original error still persists.

Baz







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Re: [R] Confused by code?

2012-09-24 Thread Bazman76
Thanks Rui Barrudas and Peter Alspach,

I understand better now:

x-matrix(c(1,0,0,0,2,0,0,0,2),nrow=3) 
 y-matrix(c(7,8,9,1,5,10,1,1,0),nrow=3) 
 z-matrix(c(0,1,0,0,0,0,6,0,0),nrow=3) 
 x[z]-y[z] 
 viewData(x)

produces an x matrix 

7   0   0
0   2   0
0   10 2

which makes sense the first element of y 7 is inserted into z in slot x[1] 
and the and 6th element of y 10 is slotted into the x[6]. 


However the original code runs like this:

mI- mRU(de.d, de.nP)de.CR
mPV[mI]mP[mI]

where mPv and MP are both (de.d, de.nP) matrices.

and

mRUlt;-function(m,n){
 return(array(runif(m*n), dim=c(m,n)))
}

i.e. it returns an array of m*n random numbers uniformly distributed between
0 and 1.

de.CR is a fixed value say 0.8.

So mIlt;- mRU(de.d, de.NP)de.CR returns a de.d*de.nP array where each
element is 1 is its more than 0.8 and zero otherwise.

So in this case element mPv[1] will be repeatedly filled with the value of
mP[1] and all other elements will remain unaffected?

Is this correct?

If so I am still confused as this is not what I thought was supposed to by
happening but I know that the code overall does its job correctly?



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[R] Confused by code?

2012-09-23 Thread Bazman76
x-matrix(c(1,0,0,0,1,0,0,0,1),nrow=3)
 y-matrix(c(0,0,0,1,0,0,1,1,0),nrow=3)
 z-matrix(c(0,1,0,0,1,0,1,0,0),nrow=3)
 x[z]-y[z]

The resultant matrix x is all zeros except for the last two diagonal cells
which are 1's.
While y is lower triangualr 0's with the remaining cells all ones.

I really don't understand how this deceptively simple looking piece of code
is giving that result can someone explain please.
I'm obviously missing something pretty basic so please keep your answer
suitably basic.



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Re: [R] Server R

2012-09-17 Thread Bazman76


Thanks Michael,
I presume that the command
sudo apt-get updatewill do the trick but am emailing the appropriate group to 
get more background on what packages are included in the latest ubuntu version 
of R.Date: Mon, 17 Sep 2012 05:43:56 -0700
From: ml-node+s789695n4643369...@n4.nabble.com
To: h_a_patie...@hotmail.com
Subject: Re: Server R



On Sun, Sep 16, 2012 at 9:42 PM, Bazman76 [hidden email] wrote:

 Hi there,



 I used the command



 sudo apt-get install r-base



 to install R on an EC2 server as shown below:



 http://www.r-bloggers.com/ec2-micro-instance-of-rstudio/


 It works but the version of R installed is:



  R.version.string

 [1] R version 2.12.1 (2010-12-16)



 I want to the latest version with package parallel included.



 How can I change the commend to ensure the latest version of R is installed?





I presume EC2 runs Ubuntu:


http://cran.r-project.org/bin/linux/ubuntu/README

Cheers,

Michael











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[R] Server R

2012-09-16 Thread Bazman76
Hi there,

I used the command

sudo apt-get install r-base

to install R on an EC2 server as shown below: 

http://www.r-bloggers.com/ec2-micro-instance-of-rstudio/

It works but the version of R installed is:

 R.version.string
[1] R version 2.12.1 (2010-12-16)

I want to the latest version with package parallel included.

How can I change the commend to ensure the latest version of R is installed?






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[R] Parallel R

2012-09-14 Thread Bazman76
Hi there,

I have a largish optimisation problem (10 years of daily observations).

I want to optimise between 4 and 6 parameters.

I'd like to utilise parallel computing if I can as I will have to run it
with different starting values etc.

I have a quad core PC with 16GB ram running windows 7.

Having done  a little reading it seems the two best options for me are:

1.) Use the academic version of REvolution R enterprise which will let me
run the code in parallel on my own PC.

2.) Or install Unubtu and use Segue and Amazon EC2 (or some equivalent).

Just to get an idea how much faster is option 2 liable to be (given that its
slightly more difficult to set up). 

Is it realistic to have a dual boot on my PC?

Thanks

Baz



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Re: [R] Parallel R

2012-09-14 Thread Bazman76
Thanks for that I hadn't realised parallel could run on windows Pc's.

The code is differential evolution but its not part of a package.

Still I would like to be able to use cloud computing if possible, any
thoughts on the easiest way to achieve that using a windows based PC?

Found this blog which seems to give pretty clear instructions:

http://travisnelson.net/2011/05/05/ec2-micro-instance-of-rstudio/

and was also recommended cloudRmpi package.

Have you experience with either of these?

 





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Re: [R] Difference between spec.pgram spec.ar

2012-04-09 Thread Bazman76
OK so I neeed to understan better what it it they are trying to measure.

I understood (incorrectly it seems) that they were simply different methods
to get the same result?

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Re: [R] Difference between spec.pgram spec.ar

2012-04-09 Thread Bazman76
oops sorry

n 08.04.2012 20:39, Bazman76 wrote: 
 Hi there, 
 
 Can someone explain what the difference between spec.pgram and spec.ar is? 
 
 I understand that they attempt to do the same thing one using an AR 
 estimation of the underlying series to estimate teh sensity the other
 using 
 the FFT. However when applied to teh same data set they seem to be giving 
 quite different results? 
 
 http://r.789695.n4.nabble.com/file/n4541358/R_example.jpg
 
 
 Clearly the spec.ar() result seems to be smoothed but the results are also 
 generally very different only really sharing the peak as the frequencies
 go 
 towards zero. 
 
 Can someone please explain why these two functions produce such different 
 results on the same data set? 
« [hide part of quote]

*Because they really measure different things? Why do you expect to get 
the same output in time as well as in frequency domain? *

Uwe Ligges 


 
 code shown below: 
 
   library(waveslim) 
 
 vols=read.csv(file=C:/Users/ocuk/My Documents/Abs Vol.csv, header=TRUE, 
 sep=,) 
 x-ts(vols[,1]) 
 #x 
 
 ## LA(8) 
 vol.la8- mra(x, la8, 4, modwt) 
 names(vol.la8)- c(d1, d2, d3, d4, s4) 
 ## plot multiresolution analysis of IBM data 
 #par(mfcol=c(6,1), pty=m, mar=c(5-2,4,4-2,2)) 
 par(mfcol=c(3,1), pty=m, mar=c(5-2,4,4-2,2)) 
 plot.ts(x, axes=F, ylab=, main=(abs rtns)) 
 #for(i in 1:5) 
 # plot.ts(vol.la8[[i]], axes=F, ylab=names(vol.la8)[i]) 
 #axis(side=1, at=seq(0,1600,by=100), 
 # labels=c(0,,200,,400,,600,,800,,1000,,1200,,1400,,1600)) 
 
 spectrum(vol.la8[[1]]) 
 specx- spec.ar(x) 
 
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« [hide part of quote]

 


*OK so I neeed to understan better what it it they are trying to measure. 

I understood (incorrectly it seems) that they were simply different methods
to get the same result?  *

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Re: [R] Difference between spec.pgram spec.ar

2012-04-09 Thread Bazman76
Yes I agree, there may be something pathalogical in the way at least one of
the models handles the data.  That's why I was trying to get a better handle
on how the two functions spec.prgm() and spec.ar() work.

The data has been processed by a wavelet analysis, so what you are seeing as
the raw data is in fact the level1 details from the wavelet anlaysis.

In theory this should only have high frequency components, that was why I am
so surpirsed to see such strong components at low frequencies.

That is not a R quesiton per se, but surely how spec.prgm() and spec.ar()
work is?



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Re: [R] Error in xy.coords(x, NULL, log = log) : (list) object cannot be coerced to type 'double'

2012-04-08 Thread Bazman76
that's it!

Thank you.

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[R] Difference between spec.pgram spec.ar

2012-04-08 Thread Bazman76
Hi there,

Can someone explain what the difference between spec.pgram and spec.ar is?

I understand that they attempt to do the same thing one using an AR
estimation of the underlying series to estimate teh sensity the other using
the FFT. However when applied to teh same data set they seem to be giving
quite different results?

http://r.789695.n4.nabble.com/file/n4541358/R_example.jpg 


Clearly the spec.ar() result seems to be smoothed but the results are also
generally very different only really sharing the peak as the frequencies go
towards zero.

Can someone please explain why these two functions produce such different
results on the same data set?

code shown below:

 library(waveslim)

vols=read.csv(file=C:/Users/ocuk/My Documents/Abs Vol.csv, header=TRUE,
sep=,)
x-ts(vols[,1])
#x

## LA(8)
vol.la8 - mra(x, la8, 4, modwt)
names(vol.la8) - c(d1, d2, d3, d4, s4)
## plot multiresolution analysis of IBM data
#par(mfcol=c(6,1), pty=m, mar=c(5-2,4,4-2,2))
par(mfcol=c(3,1), pty=m, mar=c(5-2,4,4-2,2))
plot.ts(x, axes=F, ylab=, main=(abs rtns))
#for(i in 1:5)
#   plot.ts(vol.la8[[i]], axes=F, ylab=names(vol.la8)[i])
#axis(side=1, at=seq(0,1600,by=100), 
#   
labels=c(0,,200,,400,,600,,800,,1000,,1200,,1400,,1600))

spectrum(vol.la8[[1]])
specx - spec.ar(x) 

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[R] Error in xy.coords(x, NULL, log = log) : (list) object cannot be coerced to type 'double'

2012-04-01 Thread Bazman76
Hi there,

When I run the code below I get the error

Error in xy.coords(x, NULL, log = log) :(list) object cannot be coerced to
type 'double'

Any tips how I can resolve this?

 
 library(waveslim)
 
 vols=read.csv(file=C:/Users/ocuk/My Documents/Abs Vol.csv, header=TRUE,
 sep=,)
 x-c(vols[,1])
 #x
 #data(ibm)
 av.la8 - mra(x, la8, 4, modwt)
 #names(av.la8) - c(d1, d2, d3, d4,d5,d6, d7, d8,s8)
 names(av.la8) - c(d1, d2, d3, d4,s4)
 #par(mfcol=c(10,1), pty=m, mar=c(5-2,4,4-2,2))
 par(mfcol=c(6,1), pty=m, mar=c(5-2,4,4-2,2))
 plot.ts(av.la8, axes=F, ylab=, main=abs vol)
*Error in xy.coords(x, NULL, log = log) : 
  (list) object cannot be coerced to type 'double'*
 #for(i in 1:9)
 for(i in 1:5)
+   plot.ts(av.la8[[i]], axes=F, ylab=names(av.la8)[i])
 axis(side=1, at=seq(0,1541,by=100), 
+   
labels=c(0,,200,,400,,600,,800,,1000,,1200,,1400,))

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Re: [R] a question on autocorrelation acf

2011-12-06 Thread Bazman76
http://r.789695.n4.nabble.com/file/n4164630/R_example.xlsx R_example.xlsx 

Hi there,

I attach an excel file which I use to produce the data.

It simulates a simple AR(1) process y_t=0.5y_{t-1}+z_t.

In column E I have cut and paste values so that we can compare like with
like. 

When I run the acf() on these values, it shows 3 significant lags.

When I run the pacf() it shows one very strong correlation of 0.3 at lag 1,
and a smaller one at lag 2 of around 0.05. 

Now according to the theory the pacf() results should give the correct
exponents for the lags. 
This is a pure AR(1) process so the results should be 0.5 on lag 1 and
statistically insignificant else where?

I have tried if for several realisations of the white noise term and the
results are qualatively similar and is disagreement with the theory.


Kind Regards

Baz

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Re: [R] a question on autocorrelation acf

2011-12-05 Thread Bazman76
Hi there,

I am wondering how R calculates the acf too?

I have a data set of approx 1500 returns when I calculate the lag 1
autocorrelation in excel I get a value of -0.4 but in R its approximately
-0.18?

I have cross checked with PC give and PC give agrees with excel?

I'm sure its just some kind of scaling but it would be nice to resolve this
discrepency!

Baz

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Re: [R] a question on autocorrelation acf

2011-12-05 Thread Bazman76
Hi there,

I have now cheked the results against pc give and the excel add-in poptools.

Poptools and pc give get the same answer but R is quite different especially
for the acf and pacf()?

I looked at the book you recommended on p390 itshows the formulas and they
look pretty standard.

However looking at the code that you sent the acf function does not seem to
be being calculated as shown in the book?

At no point is the series mean calculated? unless the variable x is already
demeaned in some way ie. there is some preprocessing that I need to see to
fully understand?



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Re: [R] Split an array into arbirtary sizes

2011-10-29 Thread Bazman76
sorry!

vols=read.csv(file=C:/Documents and Settings/Hugh/My
Documents/PhD/QuickDirtyVols.csv 
+  , header=TRUE, sep=,)
 x-ts(vols[,2])
 x

so I have an ts object of 500 elements.

I want to be able to split the array into say two parts of 250?

How can I do it?
I want to keep the elements in the same order



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[R] Split an array into arbirtary sizes

2011-10-28 Thread Bazman76
Hi there,

I have a ts object that I would like wo split into arbirary sizes.

Can'tfind how to do this?

I realise its probaly very simple buy I can't sem to find the right
function?


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[R] Correllogram of Daily Time Series

2011-10-27 Thread Bazman76
Hi there,

What is the best way to get a time series of daily stock price observations
into R (from excel).

The time series are daily but there are spaces for w/e's and holidays etc.
So I am not sure a ts object will be suitable but I am not sure what I
should use?

What ever package you recemmned i need to be able to run a corrolelagram.

Thanks

Hugh

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Re: [R] Correllogram of Daily Time Series

2011-10-27 Thread Bazman76
I did it using the code below thank you.

Will the fact I have used a ts object but the observations are not really
equally spaced invalidate the results?

vols=read.csv(file=C:/Documents and Settings/Hugh/My Documents/PhD/Swaption
vols.csv 
+ , header=TRUE, sep=,)
 x-ts(vols[,2])
 x

acf(x)

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[R] Confusing piece of R code

2011-07-09 Thread Bazman76
m0-epxression((4*theta1*theta2-theta3^2)/(2*x*theta3^2)-0.5*theta1*x)

params-all.vars(m0)  this reads all the params
from m0 so theta1,2 and 3 correct?
params-params[-which(params==x)]  checks which params are multiplied
by x?
np-length(params)

for(i in 1:6){
esp-get(sprintf(m%d,i-1))what does get do? sprinf
formats strings? so what is it doinf here?
assign(sprintf(m%d,i),D(esp,x)) what doeas assign so what in
sprintf doing and what does D do?
}

really really confused?

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Re: [R] Confusing piece of R code

2011-07-09 Thread Bazman76
thanks sarah


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Re: [R] Reading Data from mle into excel?

2011-05-31 Thread Bazman76
Can I use sink() to transfer the MLE results which are a S4 type object to a
text file?

Can someone show me how to do this?


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Re: [R] Reading Data from mle into excel?

2011-05-31 Thread Bazman76

Hi Greg,
 
I have about 40 time series each of which I have to run a seperate MLE on. I 
will be experimenting with different starting values for the parameters etc, so 
some way to automate the process will be useful. 
I think I can just about do this part (if you see the code above) but as I 
can't do the second part I can't check it properly. 
 
The second part I simply want to take the results of all the MLE calculation: 
the parameter estimates, there standard errors and the actual value of the 
likilihood ratio so that I can compare them and present them to my supervisor.
The last part must be done in excel as my supervisor has not been converted to 
R yet.
 
Kind Regards
 
Hugh

 


Date: Tue, 31 May 2011 08:24:08 -0700
From: ml-node+3563453-1045326083-236...@n4.nabble.com
To: h_a_patie...@hotmail.com
Subject: Re: Reading Data from mle into excel?

The sink function will write to a file what normally shows up on the screen 
after running some code.  So while it is possible to use it to capture the 
output of the mle command and read the results into excel, I don't see anything 
useful that you could then do with it in excel. 

If you can tell us more about what your ultimate goal is, what you want to do 
with the results, then we can give better advice on either how to get the 
pieces you want into excel, or probably better, how do accomplish what you want 
in R without needing to involve excel at all. 

-- 
Gregory (Greg) L. Snow Ph.D. 
Statistical Data Center 
Intermountain Healthcare 
[hidden email] 
801.408.8111 



 -Original Message- 
 From: [hidden email] [mailto:r-help-bounces@r- 
 project.org] On Behalf Of Bazman76 
 Sent: Tuesday, May 31, 2011 9:04 AM 
 To: [hidden email] 
 Subject: Re: [R] Reading Data from mle into excel? 
 
 Can I use sink() to transfer the MLE results which are a S4 type object 
 to a 
 text file? 
 
 Can someone show me how to do this? 
 
 
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Re: [R] Reading Data from mle into excel?

2011-05-24 Thread Bazman76
thanks for all your help

I have taken a slightly different route but I think I am getting there

library(plyr) 

#setwd(C:/Documents and Settings/Hugh/My Documents/PhD)

#files-list.files(C:/Documents and Settings/Hugh/My
Documents/PhD/,pattern=Swaption Vols.csv)
#vols - lapply(files, read.csv, header = TRUE) 

vols=read.csv(file=C:/Documents and Settings/Hugh/My Documents/PhD/Swaption
vols.csv 
+ , header=TRUE, sep=,)

dcOU-function(x,t,x0,theta,log=FALSE){
Ex-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t)
Vx-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2])
dnorm(x,mean=Ex,sd=sqrt(Vx),log=log)
}
OU.lik-function(theta1,theta2,theta3){
n-length(X)
dt-deltat(X)
-sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE))
}

require(stats4)
require(sde)


nc=ncol(vols)
for(i in 2:nc){
X-ts(vols[,i])
mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1),
method=L-BFGS-B,lower=c(-Inf,-Inf,-Inf),upper=c(Inf,Inf,Inf))-fit
summary(fit)
}

right now the summary(fit) gives the summary results for the 53rd column so
the code is working correctly.
How can I save these summary results in an array or datatable on each loop?

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[R] Reading Data from mle into excel?

2011-05-23 Thread Bazman76
Hi there,

I ran the following code:

vols=read.csv(file=C:/Documents and Settings/Hugh/My Documents/PhD/Swaption
vols.csv 
, header=TRUE, sep=,)
X-ts(vols[,2])
#X


dcOU-function(x,t,x0,theta,log=FALSE){
Ex-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t)
Vx-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2])
dnorm(x,mean=Ex,sd=sqrt(Vx),log=log)
}
OU.lik-function(theta1,theta2,theta3){
n-length(X)
dt-deltat(X)
-sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE))
}

require(stats4)
require(sde)
set.seed(1)
#X-sde.sim(model=OU,theta=c(3,1,2),N=1,delta=1)
mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1),
method=L-BFGS-B,lower=c(-Inf,-Inf,-Inf),upper=c(Inf,Inf,Inf))-fit
summary(fit)

#ex3.01 R
prof-profile(fit)
par(mfrow=c(1,3))
plot(prof)
par(mfrow=c(1,1))
vcov(fit)

I run the code above and I get:

 summary(fit)
Maximum likelihood estimation

Call:
mle(minuslogl = OU.lik, start = list(theta1 = 1, theta2 = 1, 
theta3 = 1), method = L-BFGS-B, lower = c(-Inf, -Inf, -Inf), 
upper = c(Inf, Inf, Inf))

Coefficients:
 Estimate  Std. Error
theta1 0.03595581 0.013929892
theta2 4.30910365 1.663781710
theta3 0.02120220 0.004067477

-2 log L: -5136.327 

I need to run the same analysis for 40 different time series.

I want to be able to collate all the estimates of theta and the associated
stadard errors and then transfer them into excel?

Can someone please point me to some R code that will allow me to do this?

Thanks



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[R] Error in backSpline.npolySpline(sp) : spline must be monotone

2011-05-23 Thread Bazman76
I get the following error:

Error in backSpline.npolySpline(sp) : spline must be monotone

Has anyone had this error before? any ideas on a workaround?


 
 vols=read.csv(file=C:/Documents and Settings/Hugh/My
 Documents/PhD/Swaption vols.csv 
+ , header=TRUE, sep=,)
 X-ts(vols[,2])
 #X
 
 
 dcOU-function(x,t,x0,theta,log=FALSE){
+ Ex-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t)
+ Vx-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2])
+ dnorm(x,mean=Ex,sd=sqrt(Vx),log=log)
+ }
 OU.lik-function(theta1,theta2,theta3){
+ n-length(X)
+ dt-deltat(X)
+ -sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE))
+ }
 
 require(stats4)
Loading required package: stats4
 require(sde)
Loading required package: sde
Loading required package: MASS
Loading required package: fda
Loading required package: splines
Loading required package: zoo

To check the errata corrige of the book, type vignette(sde.errata)

Attaching package: 'sde'

The following object(s) are masked _by_ '.GlobalEnv':

dcOU

 set.seed(1)
 #X-sde.sim(model=OU,theta=c(3,1,2),N=1,delta=1)
 mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1),
+ method=L-BFGS-B,lower=c(-Inf,-Inf,-Inf),upper=c(Inf,Inf,Inf))-fit
 summary(fit)
Maximum likelihood estimation

Call:
mle(minuslogl = OU.lik, start = list(theta1 = 1, theta2 = 1, 
theta3 = 1), method = L-BFGS-B, lower = c(-Inf, -Inf, -Inf), 
upper = c(Inf, Inf, Inf))

Coefficients:
 Estimate  Std. Error
theta1 0.03595581 0.013929892
theta2 4.30910365 1.663781710
theta3 0.02120220 0.004067477

-2 log L: -5136.327 
 
 #ex3.01 R
 prof-profile(fit)
 par(mfrow=c(1,3))
 plot(prof)
Error in backSpline.npolySpline(sp) : spline must be monotone

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[R] Problem with MLE

2011-05-17 Thread Bazman76
Hi there,

I am trying to run the following code:

 dcOU-function(x,t,x0,theta,log=FALSE){
+ Ex-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t)
+ Vx-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2])
+ dnorm(x,mean=Ex,sd=sqrt(Vx),log=log)
+ }
 OU.lik-function(theta1,theta2,theta3){
+ n-length(X)
+ dt-deltat(X)
+ ~sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE))
+ }
 
 #ex3.01.R
 require(stats4)
Loading required package: stats4
 require(sde)
Loading required package: sde
Loading required package: MASS
Loading required package: fda
Loading required package: splines
Loading required package: zoo

To check the errata corrige of the book, type vignette(sde.errata)

Attaching package: 'sde'

The following object(s) are masked _by_ '.GlobalEnv':

dcOU

 set.seed(123)
 X-sde.sim(model=OU,theta=c(3,1,2),N=1000,delta=1)

T set to = 1000.00
 mle(OU.lik,start=list(theta1=1,theta2=0.5,theta3=1),
+ method=L-BFGS-B,lower=c(-Inf,0,0))-fit
Error in optim(start, f, method = method, hessian = TRUE, ...) : 
  'pairlist' object cannot be coerced to type 'double'

but there appears to be a problem with the optimisation process?
Unfortunately it's not clear to me from the error message what is going
wrong?

Can someone please advise.

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Re: [R] Problem with MLE

2011-05-17 Thread Bazman76
sorry I solved it, was a typo on my part!!

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[R] Adding dates to time series

2011-05-15 Thread Bazman76
Hi there,

I have a spreadsheet in excel which consists of first column  of dates and
then subsequent columns that refer to prices of different securities on
those dates. (the first row contains each series name)

I saved the excel file as type csv and then imported to excel using

prices=read.csv(file=C:/Documents and Settings/Hugh/My Documents/PhD/Option
prices.csv,header = TRUE, sep = ,)

This creates the correct time series data

x-ts(prices[,2])

but does not have the dates attached.

However the dates refer to working days. So although in general they
represent Monday-Friday this is not always the case because of holidays etc.

How then can I create a time series where the dates are read in from the
first column of the csv file? I can not find an example in R documentation
where this is done?

Thanks


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Re: [R] Adding dates to time series

2011-05-15 Thread Bazman76
OK I got it to work thanks to your example

plot(ser)

however, ultiamtely a I need a stype ts object.

So I used

 xts - as.ts(ser) 
 xts
Time Series:
Start = 1 
End = 732 
Frequency = 1 

which just gets me back to where I started with the correct raw data but no
attached dates?

It is possible to have a time series ts() object with irregular dates?

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Re: [R] Adding dates to time series

2011-05-15 Thread Bazman76
additional!!

I now realise that the time series created below is in the wrong order!

clearly the column of dates are not being interpreted as dates by the R. Is
is possible for R to read column one as dates? how can I do this?

dd-data.frame(prices[,1],prices[,2])
 head(dd,3)
   prices...1.  prices...2.
1 16/12/2004 0.13675654
2 17/12/2004 0.22967560
3 20/12/2004 0.01841611
 ser-with(dd,zoo(prices[,2],prices[,1]))
 plot(ser)
 xts - as.ts(xzoo) 
Error in as.ts(xzoo) : object 'xzoo' not found
 xts - as.ts(ser) 
 xts
Time Series:
Start = 1 
End = 732 
Frequency = 1 


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[R] R won't start keeps crashing

2011-05-12 Thread Bazman76
Hi there,

I am reletively new user I only dowloaded is about a week ago.

I was getting along fine but last night I tried to selected save workspace.

Since then R will not work And I really really need it.

There are two eror massages:

The first if a pop up box is Fatal error: unable to resolve data in
.RData.

The second is a message in the GUI: Error in loadNamespace(name) there is
no package called vars.

When I click to dismiss the message box the whole thing just shuts down!!

I have tried reinstalling but it has made no difference.

Please Help





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Re: [R] R won't start keeps crashing

2011-05-12 Thread Bazman76
OK I did a seach for the files and got:

.Rdata which is 206KB
Canada.Rdata which is 3kB

If I click on .Rdata I get the crash.

If I click on Canada.Rdata the system starts?

also they are stored in different places?

.Rdata is in My documents
Canada.RData is in My Documents\vars\vars\data

I assume I should delete .Rdata, should I also delete the other file?
Where should these files be stored?

I think the .RData was a result of my trying to save the workspace. Are
there files being saved to the correct location?

Thanks for your help


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Re: [R] R won't start keeps crashing

2011-05-12 Thread Bazman76
http://r.789695.n4.nabble.com/file/n3517669/R_crash.jpg 

OK when I click on the .RData file I get the screen above. Also when I start
R from the desktop icon or from select if from programs I get the same
result.

The warning message is in focus and I can not move the focus to the GUI.
When I either click to dismiss the message of click to close it the whole
session shuts down.

So I can not enter the commands you sugested into this corrupt version.


However, when I click on the Canada.Rdata the R session starts and seems to
function normally.

Here are the results of the functions you requested. Not sure if they will
help given that this version is workfing?

 sessionInfo()
R version 2.13.0 (2011-04-13)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=English_United Kingdom.1252 
[2] LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C   
[5] LC_TIME=English_United Kingdom.1252

attached base packages:
[1] stats graphics  grDevices utils datasets  methods   base   





 load(C:/path/to/file) 
Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
In addition: Warning message:
In readChar(con, 5L, useBytes = TRUE) :
  cannot open compressed file 'C:/path/to/file', probable reason 'No such
file or directory'
 
 

Sorry if I gave you the wrong information previously, just let me know what
you want.

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Re: [R] R won't start keeps crashing

2011-05-12 Thread Bazman76
I will read the intor to R.

When closing I got a pop up asking me if I wanted to save the workspace I
just clicked yes?

here is what I got

load(C:/Documents and Settings/Hugh/My Documents/vars/vars/data)
Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
In addition: Warning message:
In readChar(con, 5L, useBytes = TRUE) :
  cannot open compressed file 'C:/Documents and Settings/Hugh/My
Documents/vars/vars/data', probable reason 'Permission denied'


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Re: [R] R won't start keeps crashing

2011-05-12 Thread Bazman76
will delete it, just wanted to try and sort out the bug

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