search for: probability

Hello. I have a quick question. I try to use logit regression, to work out probabilities in the sport event. I have work out probabilities for group of 2 players: p1 - probability, what player1 will beat player2 p2 - probability, what player2 will beat player1 pt - tie probability, p1 <- 1 - p1 - p2; Now i want to work out probabilities for group of 3 players, like: pg1 - probability, what player1 will beat player2 and player3 pg2 - probability, what player2 will beat p...

Dear R:ers, I'm using the svm from the e1071 package to train a model with the option "probabilities = TRUE". I then use "predict" with "probabilities = TRUE" and get the probabilities for the data point belonging to either class. So far all is well. My question is why I get different results each time I train the model, although I use exactly the same data.

Probability <- function(N, f, m, b, x, t) { #N is the number of lymph nodes #f is the fraction of Dendritic cells (in the correct node) that have the antigen #m is the number of time steps #b is the starting position (somewhere in the node or somewhere in the gap between nodes. It is a number between 1...

...model, and tested it against a validation data set with good results: AUC is high, and the confusion matrix indicates low commission and omission errors. The code for the best-fit model is: svm.model <-svm(as.factor(acutus)~p_feb+p_jan+p_mar+p_sep+t_feb+t_july+t_june+t_mar,cost=10000, gamma=1, probability=T) Because ultimately I want to create prediction maps of probabilities of species occurrence under future climate change, I want to use the results of the validated model to predict probability of presence using data describing future conditions. I have created a data frame (predict.data) with n...

I am a statistician and I come up to an interesting problem in cryptography. I would like to use R since there are some statistical procedures that I need to use. However, I run into a problem when using the modulus operator %%. I am using R 2.2.1 and when I calculate modulus for large numbers (that I need with my problem) R gives me warnings. For instance if one does: a=1:40; 8^a %% 41 one

...ear R Community, Below is a problem with a simple ggplot2 graph. The code returns the error message below. Error: stat_count() must not be used with a y aesthetic. My code is below and the data is attached as a ?text? file. # Graph of the probabilities library(digest) library(DT) datatable(probability) str(probability) probability$Fertilizer <- as.factor(probability$Fertilizer) str(probability) library(ggplot2) plot1 <- ggplot(probability, aes(x=Fertilizer, y=prob)) + geom_bar(aes(fill=Treatment)) plot1 Thanks. Best regards, James F. Henson -------------- next part -------------...

...), (5, 0.024), (6, 0.049), (7, 0.072), (8, 0.049), (9, 0.185), (10, 0.024), (11, 0.185), (12, 0.049), (13, 0.072), (14, 0.049)] viz. in this case I have 'bucketed' the entrant numbers against 5 representative probabilities and in subsequent computations will deem (for example) the win probability of 3 to be 0.049, so another way of visualising the result is: [((4, 5, 10), 0.024), ((3, 6, 8, 12, 14), 0.049), ((7, 13), 0.072), ((2), 0.121), ((11), 0.185)] and (3 * 0.024) + (5 * 0.049) + (2 * 0.072) + (1 x 0.121) + (1 x 0.185) ~= 1. My question is: What is the most 'correct' way...

> x <- train[,c( 2:18, 20:21, 24, 27:31)] > y <- train$out > > svm.pr <- svm(x, y, probability = TRUE, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) > > pred <- predict(svm.pr, valid[,c( 2:18, 20:21, 24, 27:31)], decision.values = TRUE, probability = TRUE) > attr(pred, "decision.values")[1:4,] 16...

I've completed an experiment and want to summarize the results. There are two things I like to create. 1) A simple count of things from the data.frame with predictions 1a) Number of predictions with probability greater than x 1b) Number of predictions with probability greater than x that are really true In SQL, this would be, "Select count(predictions) from data.frame where probability > x" "Select count(predictions) from data.frame where probability > x and labe...

svm.fit<-svm(as.factor(out) ~ ., data=all_h, method="C-classification", kernel="radial", cost=bestc, gamma=bestg, cross=10) # model fitting svm.pred<-predict(svm.fit, hh, decision.values = TRUE, probability = TRUE) # find the probability, but can not find. attr(svm.pred, "probabilities") > attr(svm.pred, "probabilities") 1 0 1 0 0 2 0 0 3 0 0 5 0 0 6 0 0 7 0 0 8 0 0 9 0 0 Hi, Dear R community, IN my data, the out variable is the target variable (...

...obabilities in the sense how do I obtain the various combinations of these two ranges along-with their respective probabilities; (ii)                             How to arrange these 9 probabilities in descending order against the respective group combination i.e. for the combination AY, the joint probability is maximum at 0.235, followed by CY at 0.202 and so on.   I sincerely apologize as perhaps I might not have raised the query properly. I have become member of this group today only and its been hardly a week since I have started learning R language. I have easily done this in Excel. My output shoul...

...am using SVM to classify categorical data and I would like the probabilities instead of the classification. ?predict.svm says that its only enabled when you train the model with it enabled, so I did that, but it didn't work. I can't even get it to work with iris. The help file shows that probability = TRUE when training the model, but doesn't show an example. Then I try to predict with probabilities, I still only get classifications back. Anyone get this to work and can help me out? Thanks, Roger attach(iris) # alternatively the traditional interface: x <- subset(iris,...

I found you online....... Can you help with empirical probability? Hi Partha. I really liked your email that you sent me, it really inspired me. I have been breezing through the chapters, and doing quite well, You should be a teacher. After all the time my college instructor spent with the class on the slopes etc.... There were very few of us who really underst...

...rix like so: (IV1) (IV2) (IV3) ... p(b0) p(b0) p(b0) p(b1) p(b1) p(b1) p(b2) p(b2) p(b2) ... where p(b1) for independent variable 1 is p(b1 != 0) (given model uncertainty - using the BMA package). i've also set it so that if the coefficient is negative, the probability is listed as negative (to be able to distinguish between significant positive and negative effects by color). i'd like to create a plot which is a 10x60 grid of rectangles, where each rectangle is colored according to its probability of being nonzero (preferably white would correspond to a z...

Hi All, When carrying out hist(samples,breaks=50,probability=TRUE), the column values are considerably greater than 1, which seams very unreasonable. The plot is attached. I think the column value of the hist plot should correspond to x$counts/sum(x$counts) (x=hist(samples,breaks=50,probability=TRUE)). The size of data is a little bit larger, causing fa...

...t A, "dA", as 3 days. We assume that "dA" is exponentially distributed. Similarly, "dB" follows an exponential distribution with average 1000 days. I decide to simulate the model with a time step corresponding to one day. Would any of the following be correct? a. A probability an individual makes transitions from A to B is 1/3. Likewise, transition from B to C occurs with probability 1/1000. b. If I reduce the size of time step as 0.1 day, then the transition probability from A to B is 0.1*(1/3). Likewise, transition probability from B to C is 0.1*(1/1000) c. The size...

https://bugzilla.netfilter.org/show_bug.cgi?id=1294 Bug ID: 1294 Summary: Strange --probability behavior Product: iptables Version: 1.4.x Hardware: x86_64 OS: All Status: NEW Severity: enhancement Priority: P5 Component: iptables Assignee: netfilter-buglog at lists.netfilter.org Report...

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X |...

Dear R users, This is a KDE beginner's question. I have this distribution: > length(cap) [1] 200 > summary(cap) Min. 1st Qu. Median Mean 3rd Qu. Max. 459.9 802.3 991.6 1066.0 1242.0 2382.0 I need to compute the sum of the values times their probability of occurence. The graph is fine, den <- density(cap, from=min(cap), to=max(cap), give.Rkern=F) plot(den) However, how do I compute sum(values*probabilities)? The probabilities produced by the density function sum to only 26%: > sum(den$y) [1] 0.2611142 Would it perhaps be ok to si...

...623.6063 3634.594 3416.350 819.6375 34 3848 ... modelFormula <- as.formula(Present ~ X02 + X03 + X05 + X06 + X07 + X13 + X14 + X15 + X18) Model <- svm( modelFormula, data=Data, gamma=0.25, cost=4, nu=0.10, kernel='radial', scale=TRUE, type='nu-regression', na.action=na.omit, probability=TRUE ) bgPreds <- predict( Model, newdata=bgEnv, type='nu-regression', probability=TRUE ) bgPreds looks like: 11 12 13 14 15 16 17 18 0.54675813 0.37587560 0.39526542 0.67043587 -0.03079247 0.16696996 0.04714134 0.06989950 19 20 0.07615735 0.14923408 Notice the negative value. I...