aicbic_plm.R

aicbic_plm <- function(object) {
    
    sp = summary(object)
    
    if(class(object)[1]=="plm"){
        u.hat <- residuals(sp) # extract residuals
        df <- cbind(as.vector(u.hat), attr(u.hat, "index"))
        names(df) <- c("resid", "Country", "Time")
        c = length(levels(df$Country)) # extract country dimension 
        t = length(levels(df$Time)) # extract time dimension 
        np = length(sp$coefficients[,1]) # number of parameters
        n.N = nrow(sp$model) # number of data
        s.sq  <- log( (sum(u.hat^2)/(n.N))) # log sum of squares
        
        if (sp$args$model == "within" & sp$args$effect == "individual"){
            n = c
            np = np+n+1 # update number of parameters
        }
        
        if (sp$args$model == "within" & sp$args$effect == "time"){
            T = t
            np = np+T+1 # update number of parameters
        }
        
        if (sp$args$model == "within" & sp$args$effect == "twoways"){
            n = c
            T = t
            np = np+n+T # update number of parameters
        }
        deviance <- s.sq
        aic <- round(       2*np  +  n.N * (  log(2*pi) + s.sq  + 1 ),1)
        bic <- round(log(n.N)*np  +  n.N * (  log(2*pi) + s.sq  + 1 ),1)
        
        list(deviance = deviance, AIC = aic, BIC = bic)
        # 
        # if(criterion=="deviance"){
        #     names(deviance) = "deviance"
        #     return(deviance)
        # }
        # if(criterion=="AIC"){
        #     names(aic) = "AIC"
        #     return(aic)
        # }
        # if(criterion=="BIC"){
        #     names(bic) = "BIC"
        #     return(bic)
        # }
    }
}