BLE_SRS {BayesSampling}  R Documentation 
Simple Random Sample BLE
Description
Creates the Bayes Linear Estimator for the Simple Random Sampling design (without replacement)
Usage
BLE_SRS(ys, N, m = NULL, v = NULL, sigma = NULL, n = NULL)
Arguments
ys 
vector of sample observations or sample mean ( 
N 
total size of the population. 
m 
prior mean. If 
v 
prior variance of an element from the population (bigger than 
sigma 
prior estimate of variability (standard deviation) within the population. If 
n 
sample size. Necessary only if 
Value
A list containing the following components:

est.beta
 BLE of Beta (BLE for every individual) 
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
Source
https://www150.statcan.gc.ca/n1/en/catalogue/12001X201400111886
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, 1528.
Examples
ys < c(5,6,8)
N < 5
m < 6
v < 5
sigma < 1
Estimator < BLE_SRS(ys, N, m, v, sigma)
Estimator
# Same example but informing sample mean and sample size instead of sample observations
ys < mean(c(5,6,8))
N < 5
n < 3
m < 6
v < 5
sigma < 1
Estimator < BLE_SRS(ys, N, m, v, sigma, n)
Estimator