ebnocov: EB Poisson-Gamma without Covariates

In saeeb: Small Area Estimation for Count Data

Description

This function gives the area level EB and MSE estimator based on Clayton & Kaldor (1987).

Usage

ebnocov(y, data, e)

Arguments

y	a response variable contains the numbers of cases in each area.
data	a mandatory data frame containing the y and e variables.
e	a variable that contains the expected numbers of cases in each area.

Details

This function only accomodates variables with count data type.

Value

The function returns a list with the following objects:

EB

data frame with number of rows equal to number of areas containing the EB estimator. For domains with zero sample size, the EB estimators are based on the synthetic regression.

Parameters

• alpha: the scale estimator in Gamma distribution

• v: the shape parameter estimator in Gamma distribution

MSE.EB

• method: Jackknife

• mse: the mean squared error estimator of the EB estimators

direct

• est: direct estimators for the response variable

• mse: the mean squared error estimator of the direct estimators

Examples

#Load dataset
data(lip)

#Save output as an object
results <- ebnocov(Y, lip, E)
results

saeeb documentation built on April 28, 2020, 5:06 p.m.