# Parametric Bootstrap Mean Squared Error of EBLUP's for domain means using Geoadditive Small Area Model This function calculates MSE of EBLUP's based on unit level using Geoadditive Small Area Model ```r pbmsegeo(formula, zspline, dom, xmean, zmean, data, B = 100) ``` ## Arguments - `formula`: the model that to be fitted - `zspline`: n*k matrix that used in model for random effect of spline-2 (n is the number of observations, and k is the number of knots used) - `dom`: a*1 vector with domain codes (a is the number of small areas) - `xmean`: a*p matrix of auxiliary variables means for each domains (a is the number of small areas, and p is the number of auxiliary variables) - `zmean`: a*k matrix of spline-2 means for each domains - `data`: data unit level that used as data frame that containing the variables named in formula and dom - `B`: the number of iteration bootstraping ## Returns This function returns a list of the following objects: - **est**: A list containing the following objects: * eblup: A Vector with a list of EBLUP with Geoadditive Small Area Model * fit: A list of components of the formed Geoadditive Small Area Model that containing the following objects such as model structure of the model, coefficients of the model, method, and residuals * sigma2: Variance (sigma square) of random effect and error with Geoadditive Small Area Model - **mse**: A vector with a list of estimated mean squared error of EBLUPs estimators ## Examples ```r #Load the dataset for unit level data(dataUnit) #Load the dataset for spline-2 data(zspline) #Load the dataset for area level data(dataArea) #Construct data frame y <- dataUnit$y x1 <- dataUnit$x1 x2 <- dataUnit$x2 x3 <- dataUnit$x3 formula <- y~x1+x2+x3 zspline <- as.matrix(zspline[,1:6]) dom <- dataUnit$area xmean <- cbind(1,dataArea[,3:5]) zmean <- dataArea[,7:12] number <- dataUnit$number area <- dataUnit$area data <- data.frame(number, area, y, x1, x2, x3) #Estimate MSE mse_geosae <- pbmsegeo(formula,zspline,dom,xmean,zmean,data,B=100) ```

pbmsegeo function