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)
 | 
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