Hi Iam looking for the cumulative distribution function for truncated poisson random variable. I can find it for the regular "poisson cdf", MATLAB gives this: p = poisscdf(x,lambda) returns the Poisson cdf at each value in x using the corresponding mean parameters in lambda Is there an analogue to a...

Hello everyone i have a list of values for which i need to get cumulative distribution function i have saved this list in a variable name yvalues [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0,...

I want to define empirical cdf in C++ according to intervals fixed by N samples received and I should save the 2 vectors (T and Y)! I made this code but it didn't work: double cum_dist_funct::real_cdf_function(vec X,double x,int N,int Ndft,vec &T, vec &Z) { Z.set_size(X.length()); Z.zeros(); vec V; V.set_size(N); V.zeros();...

Currently I am doing some cumulative distribution plot using R and I tried to set x-axis with decreasing power values (such as 10000,1000,100,10,1) in equal sizes but I failed: n<-ceiling(max(test)) qplot(1:n, ecdf(test)(1:n), geom="point",xlab="check-ins", ylab="Pr(X>=x)")+ geom_step() +scale_x_reverse(breaks=c(10000,1000,100,10,1)) +scale_shape_manual(values=c(15,19)) It seems that the output has large interval for 10000, then all the...

I apologize in advance if this is poorly worded. If I have a stdDev = 1, mean = 0, scipy.stats.cdf(-1, loc = 0, scale = 1) will give me the probability that a normally distributed random variable will be <= -1, and that is 0.15865525393145707. Given 0.15865..., how do I...

I'm struggling to use the functions MultinormalDistribution and InverseCDF in MultivariateStatistics package. Essentially << MultivariateStatistics` sig = .5; u = .5; dist = MultinormalDistribution[{0, 0}, sig*IdentityMatrix[2]]; delta=InverseCDF[dist, 1 - u] The output is InverseCDF[ MultinormalDistribution[{0, 0}, {{0.5, 0}, {0, 0.5}}], {0.5}] can someone correct the above code? If I've understood...

I have been looking for an efficient function that computes the CDF (cumulative distribution function) for the Student's t-distribution. Here's what I have settled with after looking at another stackoverflow question, JStat library, the_subtprob function on Line 317 here. Looking at the notes in the last reference led me to...

I'm looking for a function implementation (or library) in C++ that could calculate the value of the inverse of the cumulative function of a lognormal distribution. I had no luck finding it. Any help would be hugely appreciated!...

All, I have an array as follows: x=runif(1) cdf=cumsum(c(.2,.5,.1,.05,.05,.01,.09)) >p [1] 0.20 0.70 0.80 0.85 0.90 0.91 1.00 How do I return the index of the corresponding cdf entry for x? for example, .1 would return 1, .98 would return 7)...

I need to find out how to calculate the 'hypergeometric cdf': I know how the function looks like and how it works but I have a few problems tipping the function into python: def hypergeometricCDF(N,K,n,x): """ Call: p = hypergeometricCDF(N,K,n,x) Input argument: N: integer K: integer n: integer x: integer...