search for: probs

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 The prob package has been archived because it depends upon some other 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