# BLE_SSRS: Stratified Simple Random Sample BLE In BayesSampling: Bayes Linear Estimators for Finite Population

## Description

Creates the Bayes Linear Estimator for the Stratified Simple Random Sampling design (without replacement)

## Usage

 `1` ```BLE_SSRS(ys, h, N, m = NULL, v = NULL, sigma = NULL) ```

## Arguments

 `ys` vector of sample observations or sample mean for each strata (`sigma` parameter will be required in this case). `h` vector with number of observations in each strata. `N` vector with the total size of each strata. `m` vector with the prior mean of each strata. If `NULL`, sample mean for each strata will be used (non-informative prior). `v` vector with the prior variance of an element from each strata (bigger than `sigma^2` for each strata). If `NULL`, it will tend to infinity (non-informative prior). `sigma` vector with the prior estimate of variability (standard deviation) within each strata of the population. If `NULL`, sample variance of each strata will be used.

## Value

A list containing the following components:

• `est.beta` - BLE of Beta (BLE for the individuals in each strata)

• `Vest.beta` - Variance associated with the above

• `est.mean` - BLE for each individual not in the sample

• `Vest.mean` - Covariance matrix associated with the above

• `est.tot` - BLE for the total

• `Vest.tot` - Variance associated with the above

## References

GonÃ§alves, K.C.M, Moura, F.A.S and Migon, H.S.(2014). Bayes Linear Estimation for Finite Population with emphasis on categorical data. Survey Methodology, 40, 15-28.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```ys <- c(2,-1,1.5, 6,10, 8,8) h <- c(3,2,2) N <- c(5,5,3) m <- c(0,9,8) v <- c(3,8,1) sigma <- c(1,2,0.5) Estimator <- BLE_SSRS(ys, h, N, m, v, sigma) Estimator # Same example but informing sample means instead of sample observations y1 <- mean(c(2,-1,1.5)) y2 <- mean(c(6,10)) y3 <- mean(c(8,8)) ys <- c(y1, y2, y3) h <- c(3,2,2) N <- c(5,5,3) m <- c(0,9,8) v <- c(3,8,1) sigma <- c(1,2,0.5) Estimator <- BLE_SSRS(ys, h, N, m, v, sigma) Estimator ```

BayesSampling documentation built on May 2, 2021, 1:06 a.m.