* spacedim-dimensional space. For such objects, the first derivative of the
* function is a linear map from ${\mathbb R}^{\text{dim}}$ to ${\mathbb
* R}^{\text{spacedim}}$, i.e., it can be represented as a matrix
- * in ${\mathbb R}^{\text{spacedim}\times \text{dim}}. This makes sense
+ * in ${\mathbb R}^{\text{spacedim}\times \text{dim}}$. This makes sense
* since one would represent the first derivative, $\nabla f(\mathbf x)$
* with $\mathbf x\in {\mathbb R}^{\text{dim}}$, in such a way that the
* directional derivative in direction $\mathbf d\in {\mathbb R}^{\text{dim}}$
* @f}
* i.e., one needs to be able to multiply the matrix $\nabla f(\mathbf x)$ by
* a vector in ${\mathbb R}^{\text{dim}}$, and the result is a difference
- * of function values, which are in ${\mathbb R}^{\text{spacedim}}. Consequently,
+ * of function values, which are in ${\mathbb R}^{\text{spacedim}}$. Consequently,
* the matrix must be of size $\text{spacedim}\times\text{dim}$.
*
* Similarly, the second derivative is a bilinear map from ${\mathbb