Applied-Statistics---Coursework-2/model_selection.txt at master · jsjf93/Applied-Statistics---Coursework-2 · GitHub

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stepfor<-function (y = y, d = d, alfa = 0.05)
{
    pval <- NULL
    design <- NULL
    j = 1
    resul0 <- summary(lm(y ~ ., data = d))$coefficients[, 4]
    d <- as.data.frame(d[, names(resul0)[-1]])
    for (i in 1:ncol(d)) {
        sub <- cbind(design, d[, i])
        sub <- as.data.frame(sub)
        lm2 <- lm(y ~ ., data = sub)
        result <- summary(lm2)
        pval[i] <- result$coefficients[, 4][j + 1]
    }
    min <- min(pval)
    while (min < alfa) {
        b <- pval == min
        c <- c(1:length(pval))
        pos <- c[b]
        pos <- pos[!is.na(pos)][1]
        design <- cbind(design, d[, pos])
        design <- as.data.frame(design)
        colnames(design)[j] <- colnames(d)[pos]
        j = j + 1
        d <- as.data.frame(d[, -pos])
        pval <- NULL
        if (ncol(d) != 0) {
            for (i in 1:ncol(d)) {
                sub <- cbind(design, d[, i])
                sub <- as.data.frame(sub)
                lm2 <- lm(y ~ ., data = sub)
                result <- summary(lm2)
                pval[i] <- result$coefficients[, 4][j + 1]
            }
            min <- min(pval, na.rm = TRUE)
        }
        else min <- 1
    }
    if (is.null(design)) {
        lm1 <- lm(y ~ 1)
    }
    else {
        lm1 <- lm(y ~ ., data = design)
    }
    return(lm1)
}

stepback<-
function (y = y, d = d, alfa = 0.05)
{
    lm1 <- lm(y ~ ., data = d)
    result <- summary(lm1)
    max <- max(result$coefficients[, 4][-1], na.rm = TRUE)
    while (max > alfa) {
        varout <- names(result$coefficients[, 4])[result$coefficients[,
            4] == max]
        pos <- position(matrix = d, vari = varout)
        d <- d[, -pos]
        if (length(result$coefficients[, 4][-1]) == 2) {
            min <- min(result$coefficients[, 4][-1], na.rm = TRUE)
            lastname <- names(result$coefficients[, 4])[result$coefficients[,
                4] == min]
        }
        if (is.null(dim(d))) {
            d <- as.data.frame(d)
            colnames(d) <- lastname
        }
        lm1 <- lm(y ~ ., data = d)
        result <- summary(lm1)
        max <- max(result$coefficients[, 4][-1], na.rm = TRUE)
        if (length(result$coefficients[, 4][-1]) == 1) {
            max <- result$coefficients[, 4][-1]
            if (max > alfa) {
                max = 0
                lm1 <- lm(y ~ 1)
            }
        }
    }
    return(lm1)
}

position<-
function (matrix, vari)
{
    a <- colnames(matrix)
    b <- a == vari
    c <- c(1:length(a))
    d <- c[b]
    return(d)
}