datasaeu.ns {sae.prop} | R Documentation |
Data generated based on Univariate Fay Herriot Model with Additive Logistic Transformation with Non-Sampled Cases
Description
This data is generated based on univariate Fay-Herriot model and then transformed by using inverse Additive Logistic Transformation (alr). Then some domain would be edited to be non-sampled. The steps are as follows:
-
are set to be
Auxiliary variables are set as follows:
-
For random effects,
, where
.
For sampling errors
, where
is generated
.
The generated data is transformed using inverse alr transformation, so the data will be within the range of proportion.
Domain 3, 15, and 25 are set to be examples of non-sampled cases (0, 1, or NA).
-
is cluster performed using k-medoids algorithm with
pamk
.
Auxiliary variables , direct estimation
, and sampling variance
are combined into a data frame called datasaeu.
Usage
datasaeu.ns
Format
A data frame with 30 rows and 5 columns:
- y
Direct Estimation of y
- x1
Auxiliary variable of x1
- x2
Auxiliary variable of x2
- vardir
Sampling Variance of y
- cluster
Cluster of y