search for: probabilities

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 - probabi...

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. The predic...

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 and (x+t)) #x is the number of time steps it takes to traverse the gap #t is the number

...UC 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 new values for the same predictor variables used in the original model; ea...

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

Dear 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, J...

I have a list of entrants (1-14 in this example) in a competitive event and corresponding win probabilities for each entrant. [(1, 0.049), (2, 0.129), (3, 0.043), (4, 0.013), (5, 0.015), (6, 0.040), (7, 0.066), (8, 0.038), (9, 0.204), (10, 0.022), (11, 0.234), (12, 0.044), (13, 0.068), (14, 0.035)] So, of course Sum(ps) = 1. In order to make some subsequent computations more tractable, I wish...

..., 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 23 43 52 1.08157648 0.51241842 0.06234319 1.20656580 > attr(pred, "probabilities")[1:4,] NULL HI, Dear David and R community, I am trying to print out the probabilities and set a threshold for make ROC curve. I dont know why it showed NULL for the probabilities. y<-train$out, is consisting of 0 and 1 binary values. Can you help me with this? Thanks so much!...

...nt(predictions) from data.frame where probability > x and label ='T' " How can I do this one in R? 2) I'd like to create what we call "binning". It is a simple list of probability ranges and how accurate our model is. The idea is to see how "true" our probabilities are. for example range number of items mean(probability) true_accuracy 100-90% 20 .924 .90 90-80% 50 .825 .84 80-70% 214 .75...

...t<-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 (0, and 1), hh is the new data set does not contain the out variable. I trained the m...

  Dear R helpers   Suppose I have two sets of ranges (interest rates) as   Range 1 : (7 – 7.50, 7.50 – 8.50, 8.50 – 10.00) with respective probabilities 0.42, 0.22 and 0.36.     Range II : (11-12, 12-14, 14-21) with respective probabilities 0.14, 0.56 and 0.30 respectively.     My problem is to form the combinations of these ranges in a decreasing order of joint probabilities. It is assumed that these ranges are independent.   Suppose A represents...

I 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....

...object of the game is to be the first to roll various combinations of numbers (like five 5's or three of one number and two of another at the same time). This is all explained in the rules of Yahtzee. Read the rules of Yahtzee and determine the following probabilities: a. P(five 5's) = {called "five of a kind" in the game} b. P(five of any number) = {called "five of a kind"} c. P(three of one number and two of another) = {a "full house"}...

Hello! I have data containing a large number of probabilities (about 60) of nonzero coefficients to predict 10 different independent variables (in 10 different BMA models). i've arranged these probabilities in a matrix 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)...

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 failure of uploading. If you need the

...h knowledgeable and kind in this email list, and so decided to give it a try. I do stochastic simulations. Parameter values used in simulation often come from the observations of the real word phenomena. Parameter values are often given as "rates" (of change), "time", or "probabilities". I am confused about how I go about converting parameters given with different units. For example, I have a discrete time Markov model that describes the following process: A -> B -> C Let's suppose that I am given average time that individuals stay at A, "dA", as 3 day...

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

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 | Z = z). 2.Suppose that I have $I \times J$ random number

...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$y) [1] 0.2611142 Would it perhaps be ok to simply do > sum(den$x*den$y) * (1/sum(den$y)) [1] 1073.22 ? Thank you, b.

Hi All, I'm attempting to use eps-regression or nu-regression SVM to compute probabilities but the predict function applied to an svm model object returns values outside [0, 1]: Variable Data looks like: Present X02 X03 X05 X06 X07 X13 X14 X15 X18 1 0 1634 48 2245.469 -1122.0750 3367.544 11105.013 2017.306 40 23227 2 0 1402 40 2611.519 -811.2500 3422.769 10499.425 1800.475 40 13822 3 0...