normal-distribution

I have some problems with the transformation of a matrix and the names of the rows and columns. My problem is as follows: As input-matrix I have a (symmetric) correlation matrix like this one: The correlation-vector is given by the values of the lower triangular matrix: Now, I want to compute the variance-covariance-matrix of the these correlations, which are approximately normally distributed with the variance-covariance-matrix : The variances can be approximated by -> N is the sample size (in this example N = 66) The covariances can be approximated by For example the covariance between r_02

I have some data I have sampled from a radar satellite image and wanted to perform some statistical tests on. Before this I wanted to conduct a normality test so I could be sure my data was normally distributed. My data appears to be normally distributed but when I perform the test Im getting a Pvalue of 0, suggesting my data is not normally distributed. I have attached my code along with the output and a histogram of the distribution (Im relatively new to python so apologies if my code is clunky in any way). Can anyone tell me if Im doing something wrong - I find it hard to believe from my

FYI: random == pseudo-random A. when generating uniformly-random numbers, I can specify a range, i.e.: (Math.random()-Math.random())*10+5 //generates numbers between -5 and 15 B. generating a set of random values with a version of Gaussian-esque normal randomness: //pass in the mean and standard deviation function randomNorm(mean, stdev) { return Math.round((Math.random()*2-1)+(Math.random()*2-1)+(Math.random()*2-1))*stdev+mean); } //using the following values: { mean:400, standard_deviation:1 //results in a range of 397-403, or +-range of 3 }, { mean:400, standard_deviation:10 //results in a

I have been playing around with the MASS package and can plot the two bivariate normal simply using image and par(new=TRUE) for example: # lets first simulate a bivariate normal sample library(MASS) bivn <- mvrnorm(1000, mu = c(0, 0), Sigma = matrix(c(1, .5, .5, 1), 2)) bivn2 <- mvrnorm(1000, mu = c(0, 0), Sigma = matrix(c(1.5, 1.5, 1.5, 1.5), 2)) # now we do a kernel density estimate bivn.kde <- kde2d(bivn[,1], bivn[,2], n = 50) bivn.kde2 <- kde2d(bivn2[,1], bivn[,2], n = 50) # fancy perspective persp(bivn.kde, phi = 45, theta = 30, shade = .1, border = NA) par(new=TRUE) persp(bivn.kde2, phi

There is a result of some physical experiment, which can be represented as a histogram [i, amount_of(i)] . I suppose that result can be estimated by a mixture of 4 - 6 Gaussian functions. Is there a package in Python which takes a histogram as an input and returns the mean and variance of each Gaussian distribution in the mixture distribution? Original data, for example: This is a mixture of gaussians , and can be estimated using an expectation maximization approach (basically, it finds the centers and means of the distribution at the same time as it is estimating how they are mixed together).

I want to generate random numbers with a range (n to m, eg 100 to 150), but instead of purely random I want the results to be based on the normal distribution. By this I mean that in general I want the numbers "clustered" around 125. I've found this random number package that seems to have a lot of what I need: http://codeproject.com/KB/recipes/Random.aspx It supports a variety of random generators (include mersiene twister) and can apply the generator to a distribution. But I'm confused, if I use a normal distribution generator the random numbers are from roughly -6 to +8 (apparently the true

I'm trying to seed some data, is there anyway to generate numbers in SQL Server that follow a normal distribution curve? Like: I will specify the mean, the standard deviation and the count and I get a list of numbers back? quoting from http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=135026 you might try with CREATE FUNCTION [dbo].[udf_NORMSDIST] ( @x FLOAT ) RETURNS FLOAT AS /**************************************************************************************** NAME: udf_NORMSDIST WRITTEN BY: rajdaksha http://www.sqlteam.com/forums/topic.asp?TOPIC_ID=135026 DATE: 2009/10/29 PURPOSE: Mimics