Description Usage Arguments Value References See Also Examples
View source: R/Gaussian_Inference.r
For following Gaussian-NIW model structure:
mu,Sigma|m,k,v,S \sim NIW(m,k,v,S)
x|mu,Sigma \sim Gaussian(mu,Sigma)
Where NIW() is the Normal-Inverse-Wishart distribution, Gaussian() is the Gaussian distribution. See ?dNIW
and dGaussian
for the definitions of these distribution.
The sufficient statistics of a set of samples x (each row of x is a sample) are:
the effective number of samples N=nrow(x)
the sample sum xsum = colSums(x)
the uncentered scatter matrix S = t(x)
1 2 | ## S3 method for class 'GaussianNIW'
sufficientStatistics(obj, x, foreach = FALSE, ...)
|
obj |
A "GaussianNIW" object. |
x |
matrix, Gaussian samples, when x is a matrix, each row is a sample of dimension ncol(x). when x is a vector, x is length(x) samples of dimension 1. |
foreach |
logical, if foreach=TRUE, will return a list of sufficient statistics for each row of x, otherwise will return the sufficient statistics of x as a whole. |
... |
Additional arguments to be passed to other inherited types. |
If foreach=TRUE, will return a list of sufficient statistics for each row of x, otherwise will return the sufficient statistics of x as a whole.
Murphy, Kevin P. "Conjugate Bayesian analysis of the Gaussian distribution." def 1.22 (2007): 16.
Gelman, Andrew, et al. "Bayesian Data Analysis Chapman & Hall." CRC Texts in Statistical Science (2004).
GaussianNIW
, sufficientStatistics_Weighted.GaussianNIW
1 2 3 4 | x <- rGaussian(10,mu = c(-1.5,1.5),Sigma = matrix(c(0.1,0.03,0.03,0.1),2,2))
obj <- GaussianNIW() #an GaussianNIW object
sufficientStatistics(obj=obj,x=x,foreach = FALSE)
sufficientStatistics(obj=obj,x=x,foreach = TRUE)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.