typo

Author: bgctw

src/cholesky.jl

@@ -279,7 +279,7 @@ Transform a parameterization v of a blockdiagonal of upper triangular matrices
 into the this matrix.
 `cor_starts` is a NTuple of Integeres specifying the first column of each block. 
 E.g. For a matrix with a 3x3, a 2x2, and another block, 
-the blocks start at colums (1,4,6). It defaults to a single entire block.
+the blocks start at columns (1,4,6). It defaults to a single entire block.
 """
 function transformU_block_cholesky1(v::AbstractVector, cor_starts = (1,))
     cor_starts_end = (cor_starts..., length(v)+1)

src/hybrid_case.jl

@@ -142,7 +142,7 @@ Returns a NamedTuple.
 Subsets ofparameters that are correlated with other but not correlated with
 parameters of other subranges are specified by indicating the starting position
 of each subrange.
-E.g. if withing global parameter vector `(p1, p2, p3)`, `p1` and `p2` are correlated, 
+E.g. if within global parameter vector `(p1, p2, p3)`, `p1` and `p2` are correlated, 
 but parameter `p3` is not correlated with them,
 then the first subrange starts at position 1 and the second subrange starts at position 3.
 If there is only single block of all ML-predicted parameters being correlated 

test/test_doubleMM.jl

@@ -80,7 +80,7 @@ end
 
     # Pass the site-data for the batches as separate vectors wrapped in a tuple
     train_loader = MLUtils.DataLoader((xM, xP, y_o, y_unc), batchsize = n_batch)
-    # get_hybridcase_train_dataloader recreates synthetic data differetn θ_true
+    # get_hybridcase_train_dataloader recreates synthetic data different θ_true
     #train_loader = get_hybridcase_train_dataloader(case, rng; scenario)
 
     loss_gf = get_loss_gf(g, transM, f, y_global_o, int_ϕθP)