Displaying 20 results from an estimated 611 matches for "probs".

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2010 Nov 18

2

dmultinomial

Hello All,
I''m trying to run a maximum likelihood analysis using dmultinomial (i''m
avoiding dmultinom as I''d like to run it with vectors for the ML stuff).
However, I''m having a hard time getting even the simplest example
running. Any help would be greatly appreciated.
> library(mc2d)
> dmultinomial(x=c(0,0,1),prob=c(1,1,1),size=1,log=TRUE)
Error in if

2007 Jan 05

1

Efficient multinom probs

Dear R-helpers,
I need to compute probabilties of multinomial observations, eg by doing the
following:
y=sample(1:3,15,1)
prob=matrix(runif(45),15)
prob=prob/rowSums(prob)
diag(prob[,y])
However, my question is whether this is the most efficient way to do this.
In the call prob[,y] a whole matrix is computed which seems a bit of a
waste.
Is there maybe a vectorized version of dmultinom

2000 May 12

1

Geometric Distribution at prob=c(0,1)

Dear all,
I''m working with the geometric distribution for the time being, and I''m
confused. This may have more to do with statistics than R itself, but
since I''m getting results from R I find counterintuitive (well, yeah, my
statistical intuition has not been properly sharpened), I feel like
asking.
The point first:
If I do
> rgeom(1,prob=1)
I get:
[1] NaN
Warning

1998 Feb 26

7

R-beta: quantile

I do:
x<-rnorm(1000)
quantile(x,c(.025,.975))
2% 98%
-1.844753 1.931762
Since I want to find a 95% confidence interval, I take the .025 and .975
quantiles. HOWEVER R says I have the 2% (not 2.5%) and 98% (not 97.5%)
points. Is it just rounding the printed 2% and 98%, or is it REALLY
finding .02 and .98 points instead of .025 and .975?
Thanks for any help.
Bill Simpson

1998 Feb 26

7

R-beta: quantile

I do:
x<-rnorm(1000)
quantile(x,c(.025,.975))
2% 98%
-1.844753 1.931762
Since I want to find a 95% confidence interval, I take the .025 and .975
quantiles. HOWEVER R says I have the 2% (not 2.5%) and 98% (not 97.5%)
points. Is it just rounding the printed 2% and 98%, or is it REALLY
finding .02 and .98 points instead of .025 and .975?
Thanks for any help.
Bill Simpson

2017 Nov 01

1

"prob" package alternative

> On Nov 1, 2017, at 12:51 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
>
> The prob package has been archived because it depends upon some other
> packages which have issues.
>
> However, such projects as Introduction to Probability and Statistics in R
> depend upon it for learning. There are a few other resources that also use
> it.
>
> Does anyone

2017 Jun 15

1

(no subject)

Hi every one I am working on shiny app using bnlearn for Bayesian networks and using r studio I get a fatal error and when I use R GUI I get this error
** caught segfault ***
address 0xfffffffc0fcd6248, cause 'memory not mapped' Traceback: 1:
.Call("mappred", node = node, fitted = fitted, data = data, n =
as.integer(n), from = from, prob = prob, debug = debug) 2:

2017 Nov 02

1

"prob" package alternative

> On Nov 2, 2017, at 12:07 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
>
> Yes. That's the version I've been discussing that has non-zero exit status. That situation is why CRAN retired the prob package. It's possible you installed that library earlier in development and it's been "carried" along. It no longer installs, now.
>
> The problems

2017 Nov 02

1

"prob" package alternative

Yes, that is exactly what I was doing two days ago.
Warning in install.packages :
installation of package ?fAsianOptions_3010.79.tar.gz? had non-zero exit
status
Which is what a reading of the explanation for why "prob" was retired leads
one to expect. Do you have some other suggestion about how to get it to
work? I notice you're not using Windows which might have a relationship

2017 Nov 02

1

"prob" package alternative

The issue is fAsianOptions. Is there a version that works with the latest
version of R? If not, which version of it works with which version of R and
where can it be found? I tried several at the archive already.
Alternatively, is there another package that behaves similarly to prob?
On Wed, Nov 1, 2017 at 6:17 PM, David Winsemius <dwinsemius at comcast.net>
wrote:
>
> > On Nov

2017 Nov 02

1

"prob" package alternative

Yes. That's the version I've been discussing that has non-zero exit status.
That situation is why CRAN retired the prob package. It's possible you
installed that library earlier in development and it's been "carried"
along. It no longer installs, now.
The problems with all of this seem to have started this month according to
the conversations. However, no one has

2017 Nov 02

1

"prob" package alternative

> On Nov 2, 2017, at 11:15 AM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
>
> The issue is fAsianOptions. Is there a version that works with the latest version of R? If not, which version of it works with which version of R and where can it be found? I tried several at the archive already.
sessionInfo()
R version 3.4.2 Patched (2017-10-04 r73465)
Platform:

2010 Feb 14

4

Problem in performing goodness of fit test in R.

I am trying to perform goodness of fit test using R. I am using this website http://wiener.math.csi.cuny.edu/Statistics/R/simpleR/stat013.html for help. However, I am unable to carry out the test successfully. My code follows. It is taken from the website just mentioned.
freq=c(22,21,22,27,22,36) # frequencies obtained after rolling the dice 150 times.

2017 Nov 02

1

"prob" package alternative

> On Nov 2, 2017, at 1:09 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
>
> Yes, that is exactly what I was doing two days ago.
>
> Warning in install.packages :
> installation of package ?fAsianOptions_3010.79.tar.gz? had non-zero exit status
>
> Which is what a reading of the explanation for why "prob" was retired leads one to expect. Do you have

2017 Nov 02

1

"prob" package alternative

Rtools is not available for the current version of R.
What I'm looking for is an alternative package or how others have managed
to create workarounds.
On Thu, Nov 2, 2017 at 4:25 PM, David Winsemius <dwinsemius at comcast.net>
wrote:
>
> > On Nov 2, 2017, at 1:09 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
> >
> > Yes, that is exactly what I was doing

2007 Aug 22

1

"subscript out of bounds" Error in predict.naivebayes

I''m trying to fit a naive Bayes model and predict on a new data set using
the functions naivebayes and predict (package = e1071).
R version 2.5.1 on a Linux machine
My data set looks like this. "class" is the response and k1 - k3 are the
independent variables. All of them are factors. The response has 52 levels
and k1 - k3 have 2-6 levels. I have about 9,300 independent

2007 Feb 22

0

Error in solve.default

I am trying to run the following function (a hierarchical bayes linear
model) and receive the error in solve.default. The function was
originally written for an older version of SPlus. Can anyone give me some
insights into where the problem is?
Thanks
R 2.4.1 on MAC OSX 2mb ram
Mark Grant
markg at uic.edu
> attach(Aspirin.frame)
> hblm(Diff ~ 1, s = SE)
Error in solve.default(R, rinv)

2017 Nov 01

1

"prob" package alternative

The prob package has been archived because it depends upon some other
packages which have issues.
However, such projects as Introduction to Probability and Statistics in R
depend upon it for learning. There are a few other resources that also use
it.
Does anyone know of any workarounds?
Someone at stack exchange mentioned using R 2.9. However, that broke my
RStudio (WSOD) and the dependent

2017 Nov 02

1

"prob" package alternative

> On Nov 2, 2017, at 2:14 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote:
>
> Rtools is not available for the current version of R.
Really? If true, I'm surprised and not able to help. I do see an Rtools34.exe at https://cran.r-project.org/bin/windows/Rtools/
--
David.
>
> What I'm looking for is an alternative package or how others have

2013 May 23

5

sample(c(0, 1)...) vs. rbinom

Greetings. My wife is teaching an introductory stat class at UC Davis. The
class emphasizes the use of simulations, rather than mathematics, to get
insight into statistics, and R is the mandated tool. A student in the class
recently inquired about different approaches to sampling from a binomial
distribution. I''ve appended some code that exhibits the idea, the gist of
which is that