# Robust Maximum Likelihood Estimation for Spatial Error Model This package provides robust maximum likelihood estimation for spatial error model. ```r RoMLE.error( initial.beta, initial.s2, initial.lambda, W, y, x, phi.function, converge.v, iter, print.values ) ``` ## Arguments - `initial.beta`: initial value of coefficients - `initial.s2`: initial value of varaince - `initial.lambda`: initial value of autocorrelation parameters - `W`: a symmetric weight matrix - `y`: dependent variable - `x`: independent variables - `phi.function`: a robust m-estimator function, should be set as 1 for Cauchy, 2 for Welsch, 3 for Insha and 4 for Logistic - `converge.v`: converge value for fisher scoring algorithm, can be set as 1e-04 - `iter`: iteration number for fisher scoring algorithm, set by users (e.g. 100) - `print.values`: printing estimated values for each step until converge, should be set TRUE or FALSE ## Returns coefficients, lambda, s2, Phi ## Examples ```r #spdep library can be used to create a weight matrix from listw #require(spdep) #W <- as(listw, "CsparseMatrix") #example 1 data(TRQWM) data(unemployment_data) data(unemployment_coefs) y <- unemployment_data$unemployment x <- unemployment_data$urbanization #initial values was taken from MLE initial.beta <- unemployment_coefs[1:2,2] initial.lambda <- unemployment_coefs[3,2] initial.s2 <- unemployment_coefs[4,2] RoMLE.error(initial.beta, initial.s2, initial.lambda, W=TRQWM, y, x, phi.function=3, converge.v=0.0001, iter=100, print.values=TRUE) #example 2 data(TRQWM) data(IPS_data) data(IPS_coefs) y <- IPS_data[,3] x <- IPS_data[,4:10] #initial values was taken from MLE initial.beta <- IPS_coefs[1:8,2] initial.lambda <- IPS_coefs[9,2] initial.s2 <- IPS_coefs[10,2] RoMLE.error(initial.beta, initial.s2, initial.lambda, W=TRQWM, y, x, phi.function=3, converge.v=0.0001, iter=100, print.values=TRUE) ``` ## References Yildirim, V. and Kantar, Y.M. (2020). Robust estimation of spatial error model. in Journal of Statistical Computation and Simulation [https://doi.org/10.1080/00949655.2020.1740223](https://doi.org/10.1080/00949655.2020.1740223) Yildirim, V., Mert Kantar, Y. (2019). Spatial Statistical Analysis of Participants in The Individual Pension System of Turkey. Eskisehir Teknik Universitesi Bilim Ve Teknoloji Dergisi B - Teorik Bilimler, 7(2), 184-194 [https://doi.org/10.20290/estubtdb.518706](https://doi.org/10.20290/estubtdb.518706)

RoMLE.error function