Displaying 20 results from an estimated 1000 matches similar to: "function return"
2011 Mar 19
2
problem running a function
Dear people,
I'm trying to do some analysis of a data using the models by Royle & Donazio
in their fantastic book, particular the following function:
http://www.mbr-pwrc.usgs.gov/pubanalysis/roylebook/panel4pt1.fn
that applied to my data and in the console is as follows:
> `desman.y` <- structure(c(3L,4L,3L,2L,1L), .Names = c("1", "2", "3",
2009 Jan 05
2
Sweave data-figure coupling
Hi,
With the following Sweave minimal file:
---<--------------------cut here---------------start------------------->---
\documentclass{article}
\usepackage{Sweave}
\begin{document}
<<binom-sim>>=
thetas <- seq(0, 1, by=0.001)
prior <- rep(1, length(thetas)) / length(thetas)
lik <- dbinom(1, 1, thetas)
lik.p <- prior * lik
post <- lik.p / sum(lik.p)
2007 Oct 24
1
vectorized mle / optim
Hi the list,
I would need some advice on something that looks like a FAQ: the
possibility of providing vectors to optim() function.
Here is a stupid and short example summarizing the problem:
-------------------------------- example 1 ------------ 8<
----------------------
library(stats4)
data <- rnorm(100,0,1)
lik1 <- function(m, v, data) {
N <- length(data)
lik.mean <-
2012 Aug 08
1
dimnames in array
Hello,
I'm working with an array; I'm trying to make it so that an array of
dim(42,2,2) has names whose length corresponds to that of the array,
and am hoping someone with experience with this can see what I'm not
doing correctly:
data11 = array(0,c(41,2,2))
y = lsoda(x0,times,fhn$fn.ode,pars)#This is make.fhn() from colloc
infer package#
y = y[,2:3]
2006 Feb 07
1
sampling and nls formula
Hello,
I am trying to bootstrap a function that extracts the log-likelihood value and the nls coefficients from an nls object. I want to sample my dataset (pdd) with replacement and for each sampled dataset, I want to run nls and output the nls coefficients and the log-likelihood value.
Code:
x<-c(1,2,3,4,5,6,7,8,9,10)
y<-c(10,11,12,15,19,23,26,28,28,30)
pdd<-data.frame(x,y)
2007 Mar 06
2
Estimating parameters of 2 phase Coxian using optim
Hi,
My name is Laura. I'm a PhD student at Queen's University Belfast and have
just started learning R. I was wondering if somebody could help me to see
where I am going wrong in my code for estimating the parameters [mu1, mu2,
lambda1] of a 2-phase Coxian Distribution.
cox2.lik<-function(theta, y){
mu1<-theta[1]
mu2<-theta[2]
lambda1<-theta[3]
2005 Nov 11
1
optim not giving correct minima
Hello,
I am trying to use optim() on a function involving a summation. My
function basically is a thinned poisson likelihood. I have two parameters
and in most cases optim() does a fine job of getting the minima. I am
simulating my data based on pre specified parameters, so I know what I
should be getting. However when my true parameters fall in a particular
range, optim() gives
2012 Mar 14
1
Metropolis-Hastings in R
Hi all,
I'm trying to write a MH algorithm in R for a standard normal distribution,
I've been trying for a good week or so now with multiple attempts and have
finally given up trying to do it on my own as I'm beginning to run out of
time for this, would somebody please tell me what is wrong with my latest
attempt:
n=100
mu=0
sigma=1
lik<-function(theta) exp(((theta-mu)^2)/2*sigma)
2009 Feb 25
3
indexing model names for AICc table
hi folks,
I'm trying to build a table that contains information about a series of
General Linear Models in order to calculate Akaike weights and other
measures to compare all models in the series.
i have an issue with indexing models and extracting the information
(loglikehood, AIC's, etc.) that I need to compile them into the table.
Below is some sample code that illustrates my
2012 Oct 19
2
likelihood function involving integration, error in nlm
Dear R users,
I am trying to find the mle that involves integration.
I am using the following code and get an error when I use the nlm function
d<-matrix(c(1,1,0,0,0,0,0,0,2,1,0,0,1,1,0,1,2,2,1,0),nrow=10,ncol=2)
h<-matrix(runif(20,0,1),10)
integ<-matrix(c(0),nrow=10, ncol=2)
ll<-function(p){
for (k in 1:2){
for(s in 1:10){
integrand<-function(x)
2010 Sep 30
3
how to avoid NaN in optim()
hi ,
lik <- function(nO, nA, nB, nAB){
loglik <- function(par)
{
p=par[1]
q=par[2]
r <- 1 - p - q
if (c(p,q,r) > rep(0,3) && c(p,q,r) < rep(1,3) )
{
-(2 * nO * log (r) + nA * log (p^2 + 2 * p * r)
+ nB * log (q^2 + 2 * q * r)
+ nAB * (log(2) +log(p) +log(q)))
}
else
NA
}
loglik
}
2012 Oct 20
4
Error in integrate(integrand, 0, Inf) : non-finite function value
Dear R users,
When I run the code below, I get the error "Error in integrate(integrand, 0,
Inf) : non-finite function value". The code works if the function returns
only "sum(integ)". However, I want to add "cmh" to it. When I add "cmh" I
get that error. I can't figure out why this is happening because my
integrate function has nothing to do with
2011 Nov 20
2
ltm: Simplified approach to bootstrapping 2PL-Models?
Dear R-List,
to assess the model fit for 2PL-models, I tried to mimic the
bootstrap-approach chosen in the GoF.rasch()-function. Not being a
statistician, I was wondering whether the following simplification
(omit the "chi-squared-expressed model fit-step") would be appropriate:
GoF.ltm <- function(object, B = 50, ...){
liFits <- list()
for(i in 1:B){
rndDat <-
2011 May 23
6
Reading Data from mle into excel?
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)
}
2002 Jul 30
1
Optim() returns wrong maximum
Dear R-devel
During the last half a year I have several times encountered the
following problem with optim() when using method= "L-BFGS-B".
The function return a value which is clearly not the maximum (seen from
printing the value each time the function is called). Some output is
shown below.
A few things I have observed (as I remember it):
a. The problem seems to occur when the
2002 Nov 28
1
output on glm.nb
Hi,
I make a model and have compared with null model.
anova(mnull,m1)
Model theta Resid. df 2xlog-lik test df LR stat. Pr(chi)
1 ... 0.39 161 -577.9129 NA NA NA
2 ... 1.30 150 -475.6839 1 vs 2 11 102.229 1.11e10-16
anova(m1)
Df Deviance Resid. Df Resid. Dev P(>|chi|)
NULL 161 282.139 9...
... ...
2004 Sep 21
1
Problems with boot and optim
I am trying to bootstrap the parameters for a model that is estimated
through the optim() function and find that when I make the call to boot,
it runs but returns the exact same estimate for all of the bootstrap
estimates. I managed to replicate the same problem using a glm() model
but was able to fix it when I made a call to the variables as data frame
by their exact names. But no matter how I
2012 Jan 27
2
Why does the order of terms in a formula translate into different models/ model matrices?
Dear all,
I have encountered some strange things when creating lm objects in R: model
depends on the order of the terms specified in a formula.
Let us consider the following simple example:
> dat <- expand.grid(A = factor(c("a1", "a2")),
+ B = factor(paste("b", 1:4, sep="")),
+ rep = factor(1:2))
>
2012 Oct 04
1
geoRglm with factor variable as covariable
Dear R users.
I'm trying to fit a generalised linear spatial mode using the geoRglm
package. To do so, I'm preparing my data (geodata) as follow:
geoData9093 = as.geodata(data9093, coords.col= 17:18, data.col=15,*
covar.col=16*)
where covar.col is a factor variable (years in this case 90-91-92-93)).
Then I run the model as follow:
/
model.5 = list(cov.pars=c(1,1),
2012 May 31
1
Higher log-likelihood in null vs. fitted model
Two related questions.
First, I am fitting a model with a single predictor, and then a null model
with only the intercept. In theory, the fitted model should have a higher
log-likelihood than the null model, but that does not happen. See the
output below. My first question is, how can this happen?
> m
Call: glm(formula = school ~ sv_conform, family = binomial, data = dat,
weights =