Displaying 20 results from an estimated 400 matches similar to: "Problemas con la funcion "apply""
2012 Mar 15
2
Integrate inside function
Dear R users,
first I take this opportunity to greet all the R community for your
continuous efforts.
I wrote a function to calculate the pdf and cdf of a custom distribution
(mixed gamma model).
The function is the following:
pmixedgamma3 <- function(y, shape1, rate1, shape2, rate2, prev)
{
density.function<-function(x)
{
shape1=shape1
rate1=rate1
shape2=shape2
2011 Aug 01
3
Beta fit returns NaNs
Hi,
sorry for repeating the question but this is kind of important to me and i
don't know whom should i ask.
So as noted before when I do a parameter fit to the beta distr i get:
fitdist(vectNorm,"beta");
Fitting of the distribution ' beta ' by maximum likelihood
Parameters:
estimate Std. Error
shape1 2.148779 0.1458042
shape2 810.067515 61.8608126
Warning
2012 Aug 27
3
How to generate a matrix of Beta or Binomial distribution
Hi folks,
I have a question about how to efficiently produce random numbers from Beta
and Binomial distributions.
For Beta distribution, suppose we have two shape vectors shape1 and shape2.
I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from
reta(2,shape1[i]mshape2[i]). Of course this can be done via loops:
for(i in 1:10000)
{
X[i,]=rbeta(2,shape1[i],shape2[i])
}
However,
2020 Mar 26
4
unstable corner of parameter space for qbeta?
I've discovered an infelicity (I guess) in qbeta(): it's not a bug,
since there's a clear warning about lack of convergence of the numerical
algorithm ("full precision may not have been achieved"). I can work
around this, but I'm curious why it happens and whether there's a better
workaround -- it doesn't seem to be in a particularly extreme corner of
parameter
2009 Jul 01
1
Plot cumulative probability of beta-prime distribution
Hallo,
I need your help.
I fitted my distribution of data with beta-prime, I need now to plot the
Cumulative distribution. For other distribution like Gamma is easy:
x <- seq (0, 100, 0.5)
plot(x,pgamma(x, shape, scale), type= "l", col="red")
but what about beta-prime? In R it exists only pbeta which is intended only
for the beta distribution (not beta-prime)
This is
2007 Nov 13
1
TRUNCATED error with data frame
Hi ,
I am new to R.
I am trying to run a simple R script as shown below:
aov.R
------
data1<-c(49,47,46,47,48,47,41,46,43,47,46,45,48,46,47,45,49,44,44,45,42,45,45,40
,49,46,47,45,49,45,41,43,44,46,45,40,45,43,44,45,48,46,40,45,40,45,47,40)
matrix(data1, ncol= 4, dimnames = list(paste("subj", 1:12),
c("Shape1.Color1",
"Shape2.Color1", "Shape1.Color2",
2011 Jul 29
1
How to interpret Kolmogorov-Smirnov stats
Hi,
Interpretation problem ! so what i did is by using the:
>fit1 <- fitdist(vectNorm,"beta")
Warning messages:
1: In dbeta(x, shape1, shape2, log) : NaNs produced
2: In dbeta(x, shape1, shape2, log) : NaNs produced
3: In dbeta(x, shape1, shape2, log) : NaNs produced
4: In dbeta(x, shape1, shape2, log) : NaNs produced
5: In dbeta(x, shape1, shape2, log) : NaNs produced
6: In
2013 May 14
2
invalid operands of types ‘SEXPREC*’ and ‘R_len_t’ to binary ‘operator/’ with Rcpp.
Dear R-Developers,
I just started learning how to use Rcpp. Earlier while using it, I
encountered an error as shown below:
file74d8254b96d4.cpp: In function ‘Rcpp::NumericVector
foo(Rcpp::NumericVector, Rcpp::NumericVector, Rcpp::NumericVector,
Rcpp::Function, Rcpp::Function)’:
file74d8254b96d4.cpp:10: error: invalid operands of types ‘SEXPREC*’ and
‘R_len_t’ to binary ‘operator/’
make: ***
2011 Apr 07
2
Two functions as parametrs of a function.
Hi R users:
I'm trying to make a function where two of the parameters are
functions, but I don't know how to put each set of parameters for
each function.
What am I missing?
I try this code:
f2<-function(n=2,nsim=100,fun1=rnorm,par1=list(),fun2=rnorm,par2=list()){
force(fun1)
force(fun2)
force(n)
p1<-unlist(par1)
p2<-unlist(par2)
force(p1)
force(p2)
2013 Jan 22
2
Assistant
Good-day Sir,
I am R.Language users but am try to? estimate parameter of beta distribution particular dataset but give this error, which is not clear to me: (Initial value in "vmmin" is not finite)
beta.fit <- fitdistr(data,densfun=dbeta,shape1=value , shape2=value)
kindly assist.
expecting your reply:
2007 Mar 03
3
How to convert List object to function arguments?
Dear R gurus,
I have a function "goftests" that receives the following arguments:
* a vector "x" of data values;
* a distribution name "dist";
* the dots list ("...") containing a list a parameters to pass to CDF
function;
and calls several goodness-of-fit tests on the given data values against
the given distribution.
That is:
##### BEGIN CODE SNIP #####
2006 Jul 04
1
problem getting R 2.3.1 svn r38481 to pass make check-all
Hi,
I noticed this problem on my home desktop running FC4 and again on my
laptop running FC5. Both have previously compiled and passed make
check-all on 2.3.1 svn revisions from 10 days ago or so. On both these
machines, make check-all is consistently failing (4 out of 4 attempts on
the FC 4 desktop and 3 out of 3 on the FC 5 laptop) in the
p-r-random-tests tests. This is with both default
2007 Aug 16
2
(no subject)
hi,
i'm new to R and i'm trying to port a quattro pro spreadsheet into R. spreadsheets have optional lower and upper limit parameters on the beta distribution function. i would like to know how to incorporate this with R's pbeta function.
thanks in advance,
mara.
____________________________________________________________________________________
Park yourself in front of a
2007 May 03
1
Bayesian logistic regression with a beta prior (MCMClogit)
Dear all,
I am trying to use the logistic regression with MCMClogit (package:
MCMCpack/Coda) and I want to put a beta prior on the parameters, but it's
giving me error message (please see output below) no matter what shape 1 or
2 I use. It works perfect with the cauchy or normal priors. Do you know if
there is a catch there somewhere? Thanks
logpriorfun <- function(beta,shape1,shape2){
2003 Jul 04
1
Problem with fitdistr for beta
I have the following problem:
I have a vector x of data (0<x<=1 ) with
a U-shaped histogram and try to fit a beta
distribution using fitdistr. In fact,
hist(rbeta(100,0.1,0.1)) looks a lot like
my data.
The equivalent to
the example in the manual
sometimes work:
> a <- rbeta(100,0.1,0.1)
> fitdistr(x=a, "beta", start=list(shape1=0.1,shape2=0.1))1)
> shape1
2012 Mar 09
2
qbeta function in R
HI All:
Does anyone know the code behind the qbeta function in R?
I am using it to calculate exact confidence intervals and I am getting
'NaN' at places I shouldnt be. Heres the simple code I am using:
k<-3
> x<-NULL
> p<-rbeta(k,3,3)# so that the mean nausea rate is alpha/(alpha+beta)
> min<-10
> max<-60
> n<-as.integer(runif(3,min,max))
> for(i in
2011 May 03
3
fitting distributions using fitdistr (MASS)
Please guide me through to resolve the error message that I get
this is what i have done.
>x1<- rnorm(100,2,1)
>x1fitbeta<-fitdistr(x1,"beta")
Error in fitdistr(x1, "beta") : 'start' must be a named list
Yes, I do understand that sometime for the distribution to converge to the
given set of data, it requires initial parameters of the distribution, to
2013 Sep 18
1
dbeta may hang R session for very large values of the shape parameters
Dear all,
we received a bug report for betareg, that in some cases the optim call in betareg.fit would hang the R session and the command cannot be interrupted by Ctrl-C?
We narrowed down the problem to the dbeta function which is used for the log likelihood evaluation in betareg.fit.
Particularly, the following command hangs the R session to a 100% CPU usage in all systems we tried it (OS X
2012 Nov 09
1
Counting the numbers of items in vector according to their size
I am new to R and learned to program 10 years ago in C++. I am currently
working a project that looks at the distribution of randomly generated beta
values. I take 20 random beta values find their sum, repeat 100000 times.
Here is my code that it took me 4 hours to get
s=numeric(length=100000)
for(i in 1:100000){
pop=(rbeta(n=20,shape1=2,shape2=1))
s[i]=sum(pop)
}
So now I have them all in
2008 Sep 17
3
Is there a way to not use an explicit loop?
I have a problem in where i generate m independent draws from a
binomial distribution,
say
draw1 = rbinom( m , size.a, prob.a )
then I need to use each draw to generate a beta distribution. So,
like using a beta prior, binomial likelihood, and obtain beta
posterior, m many times. I have not found out a way to vectorize
draws from a beta distribution, so I have an explicit for loop