search for: probabilit

Dear list member, I struggle with the problem, why the probabilities of choosing one of three mutually exclusive alternatives don?t sum up to 1! Let?s assume we have three alternatives X, Y, and Z. Let?s further assume we know their respective utilities: uX, uY, uZ. I?m interested in calculating the probability of choosing X, Y, and Z. Since I assume that...

...TOEK) win <- ripras(steigerwald$coord) PointProcess <- ppp(x=steigerwald$coord[,1],y=steigerwald$coord[,2],window=win,marks=steigerwald$diam) plot(PointProcess) rfm.test(coord=steigerwald$coord,steigerwald$diam,MCrepetitions=19) ----- regards. Florent Bonneu Laboratoire de Statistique et Probabilit??s bureau 148 b??t. 1R2 Universit?? Toulouse 3 118 route de Narbonne - 31062 Toulouse cedex 9 bonneu at cict.fr

...ins). This works fine. T is a factored vector with levels cancer, noncancer. Proteins are numeric. Now, I want to use predict.glm to predict a new data. predict(model, newdata=testsamples, type="response") (testsamples is a small set of new samples). The result is a vector of the probabilites for each sample in testsamples. But probabilty WHAT for? To belong to the first level in T? To belong to second level in T? Is this fallowing expression factor(predict(model, newdata=testsamples, type="response") >= 0.5) TRUE, when the new sample is classified to Cancer or when it...

...an association between events A:{a,not(a)} and B:{b,not(b)} | b | not(b) | --------+-----+--------+ a | 1 | 13714 | --------+-----+--------+ not(a) | 506 | 878702 | --------+-----+--------+ I am worried that prop.test and chisq.test are not valid given the low counts and low probabilites associated with 'sucess' in each category. Is it safe to use them, and what is the alternative? (given that fisher.test can't handle this data... hold the phone... I just found fisher.test can handle this data if the test is one-tailed and not two-tailed. I don't understand the...

Maybe its slightly off-topic, but can anybody help with computing entropy on matrix of probabilities? Guess we have a matrix of probabilites, A, 2x2, something like this: z x 0 1 2 3 4 0 0.063 0.018 0.019 0.016 0.000 1 0.011 0.162 0.040 0.042 0.003 2 0.015 0.030 0.164 0.033 0.002 3 0.012 0.035 0.036 0.159 0.002 4 0.004 0.021 0.018 0.013 0.082 sum(A)=1 Can...

Hi. I have a vector of quantiles and a vector of probabilites that, when plotted, look very like the gamma cumulative distribution function. I can guess some shape and scale parameters that give a similar result, but I'd rather let the parameters be estimated. Is there a direct way to do this in R? Thanks, Tim. week <- c(0,5,6,7,9,11,14,19,3...

Hi, I am interested in using a bayesian network as a predictor (machine learning); however, I can't get any of the implementations (deal, nblearn) to learn & predict stuff. Shouldn't there also be probabilites for each node after the learning phase, how can I access these? Cheers, Stephan -- View this message in context: http://www.nabble.com/Prediction-with-Bayesian-Network--tp18220601p18220601.html Sent from the R help mailing list archive at Nabble.com.

Dear experts, I am looking for a package that does logistic regression with corssvalidation and gives me the probabilites of all the corssvalidations so that I can plot them in ROCR. Would also like to know if the corssvalidate model would give me a summary coefficient for the intercept and my to predictors. Thank you. Best regards, Jon Toledo, MD Postdoctoral fellow University of Pennsylvania School of Medicine C...

Hi, my question is probably amateurish but I can't seem to find the answer anywhere. In what metric are the MCMCglmm package's posterior means for family = "categorical"? I suppose that they can't be odds ratios and probabilites as my numbers are outside their bounds. So I'm thinking ? are they just basic regression coefficients conceptually equal to those obtained by lme4::glmer? Thank you! [[alternative HTML version deleted]]

.../04 2:14", "1/1/04 9:05") Place <- c("x1","x1","x3","x4","x5") X <- c(1,1,2,3,6) Y <- c(1,1,9,7,8) toto <- data.frame(Num,Date,Place,X,Y) Somebody know how to do ? Thanks. Florent Bonneu Laboratoire de Statistique et Probabilits bureau 148 bt. 1R2 Universit Toulouse 3 118 route de Narbonne - 31062 Toulouse cedex 9 bonneu at cict.fr <mailto:bonneu at cict.fr>

Hi, For fun, I'm trying to throw some horse racing data into either an svm or lrm model. Curious to see what comes out as there are so many published papers on this. One thing I don't know how to do is to standardize the probabilities by race. For example, if I train an LRM on a bunch of variable I get a model. I can then get probability predictions from the model. That works. It seems to me, that for a given race (8-12 horses) the probabilites of my predictions should sum to one. 1) Is there some way to train the LRM...

...on de la valeur permettant calculer le niveau de test ? 10% # Cr?ation d'une liste n11 qui contient les tailles des differents groupes n11=list() for (i in 1:q){ n11[[i]]=rep(as.integer(n/R[i]),R[i]) n11[[i]][R[i]]=n-((R[i]-1)*n11[[i]][1]) } # Cr?ation des listes P11 et P12 qui contient les probabilit?s et # les inverses des probabilites empiriques des differents groupes respectivement P11=list() P12=list() for (i in 1:q){ P11[[i]]=n11[[i]]/n P12[[i]]=n/n11[[i]] } # cr?ation d'une liste contenant les matrices W W=list() for (i in 1:q){ w=matrix(0,n,R[i]) w[1:n11[[i]][1],1]=1 for (j in 2:R...

...but Splus 2000 seems to have the same behaviour). Or perhaps I've misunderstood something. the command binom.test(11,100,p=0.1) and binom.test(9,100,p=0.1) give different p-values (see below). As 9 and 11 are equidistant from 10, the mean of the distribution, I would have thought that the probabilities should be the same. For instance, binom.test(49,50,0.5) and binom.test(51,100,0.5) do give the same results. Any help wouldbe appreciated. Jerome > binom.test(11,100,0.1) Exact binomial test data: 11 and 100 number of successes = 11, number of trials = 100, p-value = 0.7377...

...uot;%m/%d/%y %H:%M") x <- strptime(T2,"%m/%d/%y %H:%M") difftime(x,y) but, i don't know how can i do in order to obtain something like this : ans <- c(69,2,NA) res <- data.frame(T1,T2,ans) res what is to be done ? Thanks. Florent Bonneu Laboratoire de Statistique et Probabilit??s bureau 148 b??t. 1R2 Universit?? Toulouse 3 118 route de Narbonne - 31062 Toulouse cedex 9 bonneu at cict.fr

Hello Could someone please direct me to the correct commands for adding accents (grave and aigu) to a letter in a plot title, label, or in added text? I'm sure there's a handy list somewhere, but I've failed in coming up with the correct search words to find it. Thank you muchly! Jen

Hi, In continuation of the discussion of melange comments,about negative value returned in matcher due to logarithm of probabilities. *I**f we make K suitably large, we could clamp each log(K.Pi) to be >= 0, and this change will only affect really low probability terms (those with Pi < 1/K, so you can adjust K to suit):* *W' = sum(i=1,...,n, max(log(K.Pi), 0))* Did you mean for low probability the the value retur...

...in a way that return consistent result for ppois()". You have indicated one way to do so (I have just added exp() in the row): any(diff(exp(ppois(0:19, lambda=0.9, log.p=TRUE))) < 0) #[1] FALSE But may be there is another, more economic way? Serguei. > Solution: > work with log-probabilities instead. > > any(diff(ppois(0:40, lambda=0.9, log.p=TRUE))<0) > #> [1] FALSE > > I?aki > > ______________________________________________ > R-devel at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel > -- Serguei Sokol Ingenieur de...

...omework assignment. It also looks like you didn't read the documentation carefully enough. The 'len.out' argument in seq is solely for specifying the length of a sequence. The 'quantile' function omputes the empirical quantile of raw data in the vector 'x' at cumulative probabilit(y)(ies) given in the weights' argument, with interpolation I'm between. For example quantile(x=c(2.3, 1, 7, -4, 1), weights=c(0.60,0.45)) 60% 45% 1.52 1.00 So to do what you want, there may be a canned function in R but you can always write your own. First we write one that takes values...

Hi all, I was working with some probabilities and wanted to store some small values. For example: > x = 2e-250 > x [1] 2e-250 > y = 2e-300 > y [1] 2e-300 > z = 2e-350 > z [1] 0 Is there any way to store a small value (e.g. 2e-350) in R? thanks! [[alternative HTML version deleted]]

...in a way that return consistent result for ppois()". You have > indicated one way to do so (I have just added exp() in the row): > any(diff(exp(ppois(0:19, lambda=0.9, log.p=TRUE))) < 0) > #[1] FALSE > But may be there is another, more economic way? Well, log probabilites *are* very economic for many such p*() functions. OTOH, I'm a bit surprised that nobody mentioned the 'lower.tail=FALSE' option which here makes so very much sense, and is I think slightly more intuitive than the log-probabilities: It gives much much much more accurate results for s...