MAP.GaussianGaussian {bbricks} R Documentation

## Maximum A Posteriori (MAP) estimate of a "GaussianGaussian" object

### Description

Generate the MAP estimate of mu in following model structure:

x \sim Gaussian(mu,Sigma)

mu \sim Gaussian(m,S)

Where Sigma is known. Gaussian() is the Gaussian distribution. See `?dGaussian` for the definition of Gaussian distribution.
The model structure and prior parameters are stored in a "GaussianGaussian" object.
The MAP estimates are:

• (mu_MAP) = argmax p(mu|m,S,x,Sigma)

### Usage

```## S3 method for class 'GaussianGaussian'
MAP(obj, ...)
```

### Arguments

 `obj` A "GaussianGaussian" object. `...` Additional arguments to be passed to other inherited types.

### Value

numeric vector, the MAP estimate of "mu".

### References

Gelman, Andrew, et al. Bayesian data analysis. CRC press, 2013.

`GaussianGaussian`

### Examples

```obj <- GaussianGaussian(gamma=list(Sigma=matrix(c(2,1,1,2),2,2),m=c(0.2,0.5),S=diag(2)))
x <- rGaussian(100,c(0,0),Sigma = matrix(c(2,1,1,2),2,2))
ss <- sufficientStatistics(obj=obj,x=x,foreach = FALSE)
## update prior into posterior
posterior(obj = obj,ss = ss)
## get the MAP estimate of mu
MAP(obj)
```

[Package bbricks version 0.1.4 Index]