示例：对数回归

logfit

使用 logfit 函数将数据拟合到下列对数方程：

1. 定义下面的矩阵。

2. 定义估计值的矢量。

只能针对正数定义函数 ln。第二个参数会平移 x 数据以便可以计算 ln。如果 x 数据为负数，第二个估值应为正数且足够大，以便将 x 值平移到正轴。

在某些情况下，您必须调整估值，以获得可能的最佳拟合。第一个值应在大体上描述数据的高度和符号，第二个值应反映水平偏移，第三个值应反映竖直偏移。可以先绘制数据以确定估值。

3. 使用 logfit 函数找到对数拟合的参数。

第二个参数非常小。函数 lnfit 是 logfit 的理想备选函数。

4. 绘制数据和对数拟合。

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通过下面的相关系数可确认，拟合几近完美：

lnfit

使用 lnfit 函数将数据拟合到下列对数方程：

1. 调用 lnfit 可找到参数 a 和 b。

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2. 绘制数据和拟合函数。

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3. 计算相关系数。

这非常接近通过 logfit 函数实现的相关性。