distribution

问题 I have used Apple Push Notification in my apps and it works fine in Adhoc Distribution. I have submitted my apps into the AppStore, But push notification is not working for my apps and received message like "Apple rejected your device tokens". I have used separate .p12 files for development and production builds and uploaded in the Urban Airship. Note: But i have used the same application key and application master key for development and production. So that it didn't works for the push

问题 I am fairly new to c++ and boost. I want to create a set of numbers that derived from a skewed distribution using Boost's skewed_normal_distribution class. I'm not sure how to even start. I want to define a distribution with mean 0.05, variance 0.95, but a skew of 0.5. The following code doesn't work and I realise I need to set up a variate_generator as well. Can anyone provide some pointers? I am not finding the boost documentation page on skew_normal_distribution very intuitive but that

问题 Is it possible in python to generate a truncated normal distribution with a given expected value? I know that scipy.stats.truncnorm can give a truncated normal distribution that takes the mean of the original normal distribution as a parameter, but I want to create a truncated normal distribution such that the expected value of the truncated distribution is a particular value. Is this possible? 回答1: You could convert between mu and mean, see https://en.wikipedia.org/wiki/Truncated_normal

问题 I have a dataset which is in the format of frequency, direction, normalised power spectral density, spread, skewness, kurtosis I am able to visualise the distribution of a specific record using the code from the top answer in skew normal distribution in scipy but I am not sure how to apply a kurtosis value to a distribution? from scipy import linspace from scipy import pi,sqrt,exp from scipy.special import erf from pylab import plot,show def pdf(factor, x): return (100*factor)/sqrt(2*pi) *

问题 I am a novice with R. Currently I am fitting a log-normal distribution to some survival data I have, however I have become stuck when trying to calculate statistics such as the median and the mean. This is the code I have used so far, can anyone tell me what I should type next to find the mean? # rm(list=ls(all=TRUE)) library(survival) data<-read.table("M:\\w2k\\Diss\\Hoyle And Henley True IPD with number at risk known.txt",header=T) attach(data) data times_start <-c( rep(start_time_censor, n

问题 Im getting this awful and weird error when having selected an ad hoc distribution certificiate in Xcode in the Distribute for Ad Hoc section. Anyone know how to fix this error? :-) Thanks! 回答1: I just fixed the same error in my project. I'll explain the fix, and I'd love to know if it helps. I had just added the YAJL library to my iOS project. The problem was that I had followed the Mac OS X instructions, rather than the iOS. The Mac OS X instructions include the creation of a Copy Files

问题 I have a joint density function for two independent variables X and Y. And I now want to sample new x,y from this distribution. What I believe I have to do is to find the joint cumulative distribution and then somehow sample from it. I kinda know how to do this in 1D, but I find it really hard to understand how to do it in 2D. I also used the matlab function cumtrapz to find the cumulative distribution function for the above pdf. Just to be clear, what i want to do is to sample random values

问题 I'm running into a confusing part of IOS App distribution. So I need a simple breakdown of what my restrictions are, concerning distributing my App to just my workers, co-workers, or anything considered "in-house". (which is another way of stating I don't want the app on the app store) My situation is I develop for several companies, and all their employees (and some clients) will need my App to view reports. And I don't want to publish the App, just distribute it to people as they need it,

问题 I'm relatively new in R and I would appreciated if you could take a look at the following code. I'm trying to estimate the shape parameter of the Frechet distribution (or inverse weibull) using mmedist (I tried also the fitdist that calls for mmedist) but it seems that I get the following error : Error in mmedist(data, distname, start = start, fix.arg = fix.arg, ...) : the empirical moment function must be defined. The code that I use is the below: require(actuar) library(fitdistrplus)

问题 I have created an ad-hoc provision profile for my iPhone application. Everytime I add a new device, do I need to re-compile my application so that it can be distributed? This is VERY tedious. 回答1: Yes. When you compile your application it is code signed with the *.mobileprovision you have selected for the current build configuration. Each time you add a new device, it changes the *.mobileprovision file to allow for that unique UDID, so you need to both recompile AND reinstall your *