stat: address PR comments

pca_cca.go

@@ -13,9 +13,9 @@ import (
 	"github.com/gonum/matrix/mat64"
 )
 
-// PC is the result of a principal components analysis. The results of a principal
-// components analysis held by a PC are only valid after a call to PrincipalComponents
-// has returned true.
+// PC is a type for computing and extracting the principal components of a
+// matrix. The results of the principal components analysis are only valid
+// if the call to PrincipalComponents was successful.
 type PC struct {
 	n, d    int
 	weights []float64
@@ -29,11 +29,11 @@ type PC struct {
 //
 // PrincipalComponents centers the variables but does not scale the variance.
 //
-// The slice weights is used to weight the observations. If weights is nil, each
+// The weights slice is used to weight the observations. If weights is nil, each
 // weight is considered to have a value of one, otherwise the length of weights
 // must match the number of observations or PrincipalComponents will panic.
 //
-// PrincipleComponents returns whether the analysis was successful.
+// PrincipalComponents returns whether the analysis was successful.
 func (c *PC) PrincipalComponents(a mat64.Matrix, weights []float64) (ok bool) {
 	c.n, c.d = a.Dims()
 	if weights != nil && len(weights) != c.n {
@@ -66,9 +66,9 @@ func (c *PC) Vectors(dst *mat64.Dense) *mat64.Dense {
 }
 
 // Vars returns the column variances of the principal component scores,
-// b * vecs where b is a matrix with centered columns. Variances are returned
-// in descending sort order.
-// If dst is not nil is is used to store the variances and returned.
+// b * vecs, where b is a matrix with centered columns. Variances are returned
+// in descending order.
+// If dst is not nil it is used to store the variances and returned.
 // Vars will panic if the receiver has not successfully performed a principal
 // components analysis or dst is not nil and the length of dst is not min(n, d).
 func (c *PC) Vars(dst []float64) []float64 {