agaussian {MAPCtools} | R Documentation |
Aggregate Gaussian data
Description
Aggregates Gaussian data using sufficient statistics for Gaussian samples.
For a sample \boldsymbol{y} = \{y_1, \dots, y_n\}
with y_i \sim \mathcal{N(\mu, (s_i \tau)^{-1})}
, i=1, \dots, n
, the sample is aggregated into the sufficient statistic
(v, \frac{1}{2} \sum_{i=1}^n \log(s_i), m, n, \bar{y})
,
with
m = \sum_{i=1}^n s_i
\quad
\bar{y} = \frac{1}{m} \sum{i=1}^n s_iy_i
\quad
v = \frac{1}{m} \sum_{i=1}^n s_i y_i^2 - \bar{y}^2
.
For a short derivation of the sufficient statistic, attach the INLA package (library(INLA)
) and run inla.doc("agaussian")
.
Usage
agaussian(data, precision.scale = NULL)
Arguments
data |
Gaussian data, must be a numeric vector. |
precision.scale |
Scales for the precision of each Gaussian observation. |
Value
Aggregated Gaussian data, in an inla.mdata
object, which is compatible with the agaussian
family in INLA.