Test

examples/plot_fpca.py

@@ -31,7 +31,7 @@
 # main modes of variation across the function (the directions in which the
 # curves vary the most). FPCA can be though of as a basis expansion, but what 
 # distinguishes FPCA is that among all basis expansions that use K components
-# for a fixed K, the FPC expansion explains most of the variation in X.
+# for a fixed K, the FPCA expansion explains most of the variation in X.
 #
 # For more information abour FPCA and its objectives, see 
 # :footcite:ts:`wang+chiou+muller_2016_fpca`.