sufficientStatistics_Weighted.GaussianNIG {bbricks}R Documentation

Weighted sufficient statistics of a "GaussianNIG" object


For following Gaussian-NIG model structure:

x \sim Gaussian(X beta,sigma^2)

sigma^2 \sim InvGamma(a,b)

beta \sim Gaussian(m,sigma^2 V)

Where X is a row vector, or a design matrix where each row is an obervation. InvGamma() is the Inverse-Gamma distribution, Gaussian() is the Gaussian distribution. See ?dInvGamma and dGaussian for the definitions of these distribution.
The model structure and prior parameters are stored in a "GaussianNIG" object.
This object will be used as a place for recording and accumulating information in the related inference/sampling functions such as posterior(), posteriorDiscard(), MAP(), marginalLikelihood(), dPosteriorPredictive(), rPosteriorPredictive() and so on.
The sufficient statistics of a set of samples (x,X) and weights ware:


## S3 method for class 'GaussianNIG'
sufficientStatistics_Weighted(obj, x, w, X, foreach = FALSE, ...)



A "GaussianNIG" object.


numeric, must satisfy length(x) = nrow(X).


numeric, sample weights.


matrix, must satisfy length(x) = nrow(X).


logical, if foreach=TRUE, will return a list of sufficient statistics for each (x,X), otherwise will return the sufficient statistics 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,X), otherwise will return the sufficient statistics of (x,X) as a whole.


Banerjee, Sudipto. "Bayesian Linear Model: Gory Details." Downloaded from http://www. biostat. umn. edu/~ph7440 (2008).

See Also

GaussianNIG, sufficientStatistics.GaussianNIG


obj <- GaussianNIG(gamma=list(m=0,V=1,a=1,b=0))
X <- 1:20
x <- rnorm(20)+ X*0.3
w <- runif(20)
sufficientStatistics_Weighted(obj = obj,X=X,x=x,w=w)
sufficientStatistics_Weighted(obj = obj,X=X,x=x,w=w,foreach = TRUE)

[Package bbricks version 0.1.4 Index]