Displaying 20 results from an estimated 20000 matches similar to: "how to fit a model that is nonlinear with multiplicate errors"
2006 Mar 01
0
[Fwd: Re: [R] a strange problem with integrate()]
When I saw the subject of the original message on
R-help, I was 95% confident that I knew the answer
(before I had seen the question).
This made me think that perhaps for some functions
there should be a 'Troubleshooting' section in the help
file.
The current help file for 'integrate' does say, as Sundar
points out, what the requirements are. However, I
think more people would
2006 Mar 01
1
a strange problem with integrate()
Dear all,
I am stuck on the following problem with integrate(). I have been out of
luck using RSiteSearch()..
My function is
g2<-function(b,theta,xi,yi,sigma2){
xi<-cbind(1,xi)
eta<-drop(xi%*%theta)
num<-exp((eta + rep(b,length(eta)))*yi)
den<- 1 + exp(eta + rep(b,length(eta)))
result=(num/den)*exp((-b^2)/sigma2)/sqrt(2*pi*sigma2)
2006 Sep 28
1
Nonlinear fitting - reparametrization help
Hi,
I am trying to fit a function of the form:
y = A0 + A1 * exp( -0.5* ( (X - Mu1) / Sigma1 )^2 ) - A2 * exp ( -0.5*
( (X-Mu2)/Sigma2 )^2 )
i.e. a mean term (A0) + a difference between two gaussians.
The constraints are A1,A2 >0, Sigma1,Sigma2>0, and usually Sigma2>Sigma1.
The plot looks like a "Mexican Hat".
I had trouble (poor fits) fitting this function to toy data
2012 Jul 02
0
Fit circle with R
Dear Researchers,
I wrote two function to fit a circle using noisy data.
1- the fitCircle() is derived from MATLAB code of * zhak Bucher* from the
link
http://www.mathworks.com/matlabcentral/fileexchange/5557-circle-fit/content/circfit.m
2- the CircleFitByPratt() from MATLAB code of *Nikolai Chernov *from the
link
2012 Jul 03
0
need help EM algorithm to find MLE of coeff in mixed effects model
Dear All,
have a general question about coefficients estimation of the mixed model.
I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni);
b follows
N(0,\psi) #i.e. bivariate normal
where b is the latent variable, Z and X are ni*2 design matrices, sigma is
the error variance,
Y are longitudinal data, i.e. there are ni
2013 Apr 22
0
Copula fitMdvc:
Hello,
I am trying to do a fit a loglikelihood function with Multivariate
distribution via copulas with fitMdvc. The problem is that it
doesn't recognize that my beta is a vector of km parameter and when I try
to run it it say that the length of my initial values is not the same as
the parameter.
Can somebody guide me where my mistake is.
Thanks,
Elisa.
#################################
2013 May 16
2
R looping help
Hey I'm not really sure what I should put on here, but I am having trouble
with my R code. I am trying to get the p-values, R^2s etc for a number of
different groups of variables that are all in one dataset.
This is the code:
#Stand counter
st<-1
#Collections
stands<-numeric(67)
slopes<-numeric(67)
intercepts<-numeric(67)
mses<-numeric(67)
rsquares<-numeric(67)
2015 May 15
0
[RFC V3 5/8] aarch64: celt_pitch_xcorr: Fixed point intrinsics
Optimize celt_pitch_xcorr function (for fixed point).
Even though same code in theory should work for ARMv7
as well, turning this on only for aarch64 at the moment since
there is a fixed point asm implementation for ARMv7 neon.
Signed-off-by: Viswanath Puttagunta <viswanath.puttagunta at linaro.org>
---
celt/arm/celt_neon_intr.c | 268 ++++++++++++++++++++++++++++++++++++++++++++++
2014 Dec 19
0
[PATCH v1] armv7: celt_pitch_xcorr: Introduce ARM neon intrinsics
Optimize celt_pitch_xcorr function (for floating point)
using ARM NEON intrinsics for SoCs that have NEON VFP unit.
To enable this optimization, use --enable-intrinsics
configure option.
Compile time and runtime checks are also supported to make sure
this optimization is only enabled when the compiler supports
neon intrinsics.
---
Makefile.am | 12 ++
2015 May 08
0
[[RFC PATCH v2]: Ne10 fft fixed and previous 5/8] aarch64: celt_pitch_xcorr: Fixed point intrinsics
Optimize celt_pitch_xcorr function (for fixed point).
Even though same code in theory should work for ARMv7
as well, turning this on only for aarch64 at the moment since
there is a fixed point asm implementation for ARMv7 neon.
Signed-off-by: Viswanath Puttagunta <viswanath.puttagunta at linaro.org>
---
celt/arm/celt_neon_intr.c | 268 ++++++++++++++++++++++++++++++++++++++++++++++
2014 Dec 19
2
[PATCH v1] armv7: celt_pitch_xcorr: Introduce ARM neon intrinsics
On 19 December 2014 at 17:25, Viswanath Puttagunta
<viswanath.puttagunta at linaro.org> wrote:
> Optimize celt_pitch_xcorr function (for floating point)
> using ARM NEON intrinsics for SoCs that have NEON VFP unit.
>
> To enable this optimization, use --enable-intrinsics
> configure option.
>
> Compile time and runtime checks are also supported to make sure
> this
2014 Dec 10
0
[RFC PATCH v3] armv7: celt_pitch_xcorr: Introduce ARM neon intrinsics
Optimize celt_pitch_xcorr function (for floating point)
using ARM NEON intrinsics for SoCs that have NEON VFP unit.
To enable this optimization, use --enable-intrinsics
configure option.
Compile time and runtime checks are also supported to make sure
this optimization is only enabled when the compiler supports
neon intrinsics.
---
Makefile.am | 12 ++
2014 Dec 07
0
[RFC PATCH v2] armv7: celt_pitch_xcorr: Introduce ARM neon intrinsics
Optimize celt_pitch_xcorr function (for floating point)
using ARM NEON intrinsics for SoCs that have NEON VFP unit.
To enable this optimization, use --enable-intrinsics
configure option.
Compile time and runtime checks are also supported to make sure
this optimization is only enabled when the compiler supports
neon intrinsics.
---
Makefile.am | 11 ++
2001 Sep 17
0
variance of a linear model
Hi,
this question may be off topic:
the unbiased estimator of the variance of the errors in a
linear regression moedel with p coefficients is:
sigma2=sum((y-yi)^2)/(length(y)-p-1)
But what if i estimate transformations of the dependent an
independent variables (e.g. Box-Cox) too? May I calculate
the variance using
sigma2=sum((y-yi)^2)/(length(y)-2*p-1)
or should I use the first formula
2012 Jul 03
2
EM algorithm to find MLE of coeff in mixed effects model
I have a general question about coefficients estimation of the mixed model.
I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni);
b follows
N(0,\psi) #i.e. bivariate normal
where b is the latent variable, Z and X are ni*2 design matrices, sigma is
the error variance,
Y are longitudinal data, i.e. there are ni
2017 Jun 14
3
about fitting a regression line
Hi R users,
I have some data points (Xi, Yi), and they may follow such a pattern Yi =
cCOS(Xi) + d, how to find the c and d in R? which function to use? Also,
how to get the R2 and p value for this correlation? Thanks for any kind of
help.
[[alternative HTML version deleted]]
2011 Jan 27
1
Minor typo in influence.measures.Rd ?
Dear list,
There is, I believe, a minor typo in the example section of
influence.measures.Rd. In the final example the word `does` appears
where I suspect `dose` is required:
I couldn't remember exactly what format patches should be in, so here is
one as diff would produce:
Index: devel/src/library/stats/man/influence.measures.Rd
2007 Jun 14
3
how to fit y=m*x
Hi There,
I have a set of data (xi,yi).I want to fit them with the equation
y=mx.
note: in the above equation, there is no intercept.
I don't know how to use common software such as R , matlab, sas, or
spss to do this kind of regression.
Does anyone know how to do this?
I know it is easy to use least square method to do this by
programming. But I want to find if there exists some common
2017 Jun 14
0
about fitting a regression line
Start with the lm() function; i.e., see
?lm
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
On 6/14/17, 3:40 PM, "R-help on behalf of lily li" <r-help-bounces at r-project.org on behalf of chocold12 at gmail.com> wrote:
Hi R users,
I have some data points (Xi, Yi), and they may follow such a
2011 Dec 02
1
1.6x speedup for requal() function (in R/src/main/unique.c)
Hi,
FWIW:
/* Taken from R/src/main/unique.c */
static int requal(SEXP x, int i, SEXP y, int j)
{
if (i < 0 || j < 0) return 0;
if (!ISNAN(REAL(x)[i]) && !ISNAN(REAL(y)[j]))
return (REAL(x)[i] == REAL(y)[j]);
else if (R_IsNA(REAL(x)[i]) && R_IsNA(REAL(y)[j])) return 1;
else if (R_IsNaN(REAL(x)[i]) && R_IsNaN(REAL(y)[j])) return 1;