PHPでExcelの統計関数を実装

コード

/**
 * 単純平均を取得する
 */
function s_average($list) {
		$sum = NULL;
    if(count($list) < 2 || !is_array($list)){
        return false;
    }
    $count = count($list);
    for ($i = 0; $i < $count; $i++) {
        $sum += $list[$i];
    }
    return $sum / $count;
}
/**
 * 調和平均を取得する
 */
function s_harmean($list) {
		$sum = NULL;
    if(count($list) < 2 || !is_array($list)){
        return false;
    }
    $count = count($list);
    for ($i = 0; $i < $count; $i++) {
        $sum += 1 / $list[$i];
    }
    return $count / $sum;
}
/**
 * 分散を取得する
 * (引数を母集団全体であると仮定して、母集団の分散を返す)
 */
function s_varp($list) {
    if(count($list) < 2 || !is_array($list)){
        return false;
    }
    $avg = s_average($list);
    $dec = 0;
    $count = count($list);
    for($i = 0; $i < $count; $i++){
        $dec += pow($avg - $list[$i], 2);
    }
    return $dec / $count;
}
/**
 * 標準偏差を取得する
 */
function s_stdevp($list) {
    if(count($list) < 2 || !is_array($list)){
        return false;
    }
    return sqrt(s_varp($list));
}
/**
 * 偏差値を取得する
 */
function s_devp($list, $val) {
    if(count($list) < 2 || !is_array($list)){
        return false;
    }
    return 10 * ($val - s_average($list)) / s_stdevp($list) + 50;
}
/**
 * 相関係数を取得する
 */
function s_correl($list_y, $list_x){
    if(count($list_x) < 2 || count($list_y) < 2 || count($list_x) != count($list_y)){
        return false;
    }
    $avg_x = s_average($list_x);
    $stdevp_x = s_stdevp($list_x);
    $avg_y = s_average($list_y);
    $stdevp_y = s_stdevp($list_y);
    
    $count = count($list_x);
    for($i = 0; $i < $count; $i++){
        $x = $list_x[$i] - $avg_x;
        $y = $list_y[$i] - $avg_y;
        $devsum[$i] = $x * $y;
    }
    
    $avg_devsum = s_average($devsum);
    return $avg_devsum / ($stdevp_x * $stdevp_y);
}
/**
 * 回帰直線のｙ切片を求める
 * （[y = a * x + b]の[b]を求める）
 */
function s_intercept($list_y, $list_x){
		$x_sum = NULL;
		$y_sum = NULL;
		$xx_sum = NULL;
		$xy_sum = NULL;
    if(count($list_x) < 2 || count($list_y) < 2 || count($list_x) != count($list_y)){
        return false;
    }
    $count = count($list_x);
    for ($i = 0; $i < $count; $i++) {
        $x = $list_x[$i];
        $y = $list_y[$i];
        $x_sum += $x;
        $y_sum += $y;
        $xx_sum += $x * $x;
        $xy_sum += $x * $y;
    }
    $a = ($count * $xy_sum - $x_sum * $y_sum)/($count * $xx_sum - $x_sum * $x_sum);
    $b = ($y_sum - $a * $x_sum)/$count;
    
    return $b;
}
/**
 * 回帰直線の傾きを求める
 * （[y = a * x + b]の[a]を求める）
 */
function s_slope($list_y, $list_x){
		$x_sum = NULL;
		$y_sum = NULL;
		$xx_sum = NULL;
		$xy_sum = NULL;
    if(count($list_x) < 2 || count($list_y) < 2 || count($list_x) != count($list_y)){
        return false;
    }
    $count = count($list_x);
    for ($i = 0; $i < $count; $i++) {
        $x = $list_x[$i];
        $y = $list_y[$i];
        $x_sum += $x;
        $y_sum += $y;
        $xx_sum += $x * $x;
        $xy_sum += $x * $y;
    }
    $a = ($count * $xy_sum - $x_sum * $y_sum)/($count * $xx_sum - $x_sum * $x_sum);
    $b = ($y_sum - $a * $x_sum)/$count;
    
    return $a;
}
/**
 * 回帰直線上でｘに対応するｙを求める
 */
function s_forecast($target_x, $list_y, $list_x){
    if(count($list_x) < 2 || count($list_y) < 2 || count($list_x) != count($list_y)){
        return false;
    }
    $a = s_slope($list_y, $list_x);
    $b = s_intercept($list_y, $list_x);
    
    return $a * $target_x + $b;
}
/**
 * 回帰直線上の上昇率を求める
 */
function s_rate($list_y, $list_x){
    if(count($list_x) < 2 || count($list_y) < 2 || count($list_x) != count($list_y)){
        return false;
    }
    $a = s_slope($list_y, $list_x);
    $b = s_intercept($list_y, $list_x);
    
    return ($a * $list_x[count($list_x) - 1] + $b) / ($a * $list_x[count($list_x) - 2] + $b);
}

$data = array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);

$target = 47;

for ($i=0; $i<=100; $i++) {
    $ary1[] = rand(0, 100);
    $ary2[] = rand(0, 100);
}

echo "単純平均: ".s_average($data)."\n";
echo "調和平均: ".s_harmean($data)."\n";
echo "分散: ".s_varp($data)."\n";
echo "標準偏差: ".s_stdevp($data)."\n";
echo "偏差値: ".s_devp($data,$target)."\n";
echo "相関係数: ".s_correl($ary2,$ary1)."\n";
echo "回帰直線のｙ切片: ".s_intercept($ary2,$ary1)."\n";
echo "回帰直線の傾き: ".s_slope($ary2,$ary1)."\n";
echo "回帰直線上でｘに対応するｙ: ".s_forecast($target,$ary2,$ary1)."\n";
echo "回帰直線上の上昇率: ".s_rate($ary2,$ary1)."\n";