diff --git a/src/FSharp/Fit.fs b/src/FSharp/Fit.fs
index 4a15502c..4497b7ad 100644
--- a/src/FSharp/Fit.fs
+++ b/src/FSharp/Fit.fs
@@ -62,7 +62,7 @@ module Fit =
     let linear functions (x:_[]) (y:float[]) =
         functions
         |> List.map (fun f -> List.init (Array.length x) (fun i -> f x.[i]))
-        |> DenseMatrix.ofColumnsList (Array.length x) (List.length functions)
+        |> DenseMatrix.ofColumnList (Array.length x) (List.length functions)
         |> fun m -> m.QR(QRMethod.Thin).Solve(DenseVector(y)).ToArray()
         |> List.ofArray
 
diff --git a/src/FSharp/LinearAlgebra.Double.Matrix.fs b/src/FSharp/LinearAlgebra.Double.Matrix.fs
index 5508935c..6ad192b4 100644
--- a/src/FSharp/LinearAlgebra.Double.Matrix.fs
+++ b/src/FSharp/LinearAlgebra.Double.Matrix.fs
@@ -36,6 +36,8 @@ open MathNet.Numerics.LinearAlgebra
 [<CompilationRepresentation(CompilationRepresentationFlags.ModuleSuffix)>]
 module Matrix =
 
+    // TODO: generalize or reconsider
+
     /// Returns the sum of all elements of a matrix.
     let inline sum (A: #Matrix<float>) = A |> Matrix.foldnz (+) 0.0
 
@@ -75,19 +77,28 @@ module DenseMatrix =
     /// Create a matrix with the given dimension and set all values to x.
     let inline create (rows: int) (cols: int) x = DenseMatrix.Create(rows, cols, fun i j -> x) :> _ Matrix
 
+    /// Create a matrix with the given dimension and set all diagonal values to x. All other values are zero.
+    let inline createDiag (rows: int) (cols: int) x =
+        let A = DenseMatrix(rows,cols)
+        for i=0 to min (rows-1) (cols-1) do A.At(i,i,x)
+        A :> _ Matrix
+
     /// Initialize a matrix by calling a construction function for every element.
     let inline init (rows: int) (cols: int) (f: int -> int -> float) = DenseMatrix.Create(rows, cols, fun i j -> f i j) :> _ Matrix
 
+    /// Initialize a matrix by calling a construction function for every diagonal element. All other values are zero.
+    let inline initDiag (rows: int) (cols: int) (f: int -> float) =
+        let A = DenseMatrix(rows,cols)
+        for i=0 to min (rows-1) (cols-1) do A.At(i,i,f i)
+        A :> _ Matrix
+
+    /// Create an identity matrix with the given dimension.
+    let inline identity (rows: int) (cols: int) = createDiag rows cols 1.0
+
+
     /// Create a matrix from a 2D array of floating point numbers.
     let inline ofArray2 array = DenseMatrix.OfArray(array) :> _ Matrix
 
-    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
-    /// If the dimensions are known, consider to use ofRowSeq instead to avoid multiple enumeration.
-    let inline ofSeq (fss: #seq<#seq<float>>) =
-        let n = Seq.length fss
-        let m = Seq.length (Seq.head fss)
-        DenseMatrix.OfRowsCovariant(n, m, fss) :> _ Matrix
-
     /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
     /// If the dimensions are known, consider to use ofRowList instead to avoid multiple enumeration.
     let inline ofList (fll: float list list) =
@@ -96,38 +107,39 @@ module DenseMatrix =
         DenseMatrix.OfRowsCovariant(n, m, fll) :> _ Matrix
 
     /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
-    let inline ofRows (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfRowsCovariant(rows, cols, fss) :> _ Matrix
+    /// If the dimensions are known, consider to use ofRowSeq instead to avoid multiple enumeration.
+    let inline ofSeq (fss: #seq<#seq<float>>) =
+        let n = Seq.length fss
+        let m = Seq.length (Seq.head fss)
+        DenseMatrix.OfRowsCovariant(n, m, fss) :> _ Matrix
 
-    /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
-    let inline ofRowsList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfRowsCovariant(rows, cols, fll) :> _ Matrix
 
     /// Create a matrix from a list of row vectors.
-    let inline ofRowVectors (vectors: #Vector<float> list) = DenseMatrix.OfRowVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
+    let inline ofRows (vectors: #Vector<float> list) = DenseMatrix.OfRowVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
 
-    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
-    let inline ofColumns (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfColumnsCovariant(rows, cols, fss) :> _ Matrix
+    /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
+    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfRowsCovariant(rows, cols, fll) :> _ Matrix
 
-    /// Create a matrix from a list of float lists. Every list in the master list specifies a column.
-    let inline ofColumnsList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfColumnsCovariant(rows, cols, fll) :> _ Matrix
+    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
+    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfRowsCovariant(rows, cols, fss) :> _ Matrix
 
     /// Create a matrix from a list of column vectors.
-    let inline ofColumnVectors (vectors: #Vector<float> list) = DenseMatrix.OfColumnVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
+    let inline ofColumns (vectors: #Vector<float> list) = DenseMatrix.OfColumnVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
 
-    /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
-    let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = DenseMatrix.OfIndexed(rows, cols, fs) :> _ Matrix
+    /// Create a matrix from a list of float lists. Every list in the master list specifies a column.
+    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfColumnsCovariant(rows, cols, fll) :> _ Matrix
+
+    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
+    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfColumnsCovariant(rows, cols, fss) :> _ Matrix
 
     /// Create a matrix with a given dimension from an indexed list of row, column, value tuples.
     let inline ofListi (rows: int) (cols: int) (fl: list<int * int * float>) = DenseMatrix.OfIndexed(rows, cols, Seq.ofList fl) :> _ Matrix
 
-    /// Create a square matrix with constant diagonal entries.
-    let inline constDiag (n: int) (f: float) =
-        let A = DenseMatrix(n,n)
-        for i=0 to n-1 do
-            A.At(i,i,f)
-        A :> _ Matrix
+    /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
+    let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = DenseMatrix.OfIndexed(rows, cols, fs) :> _ Matrix
 
     /// Create a square matrix with the vector elements on the diagonal.
-    let inline diag (v: #Vector<float>) =
+    let inline ofDiag (v: #Vector<float>) =
         let n = v.Count
         let A = DenseMatrix(n,n)
         A.SetDiagonal(v)
@@ -152,9 +164,25 @@ module SparseMatrix =
     /// Create an all-zero matrix with the given dimension.
     let inline zeroCreate (rows: int) (cols: int) = SparseMatrix(rows, cols) :> _ Matrix
 
+    /// Create a matrix with the given dimension and set all diagonal values to x. All other values are zero.
+    let inline createDiag (rows: int) (cols: int) x =
+        let A = SparseMatrix(rows,cols)
+        for i=0 to min (rows-1) (cols-1) do A.At(i,i,x)
+        A :> _ Matrix
+
     /// Initialize a matrix by calling a construction function for every element.
     let inline init (rows: int) (cols: int) (f: int -> int -> float) = SparseMatrix.Create(rows, cols, fun n m -> f n m) :> _ Matrix
 
+    /// Initialize a matrix by calling a construction function for every diagonal element. All other values are zero.
+    let inline initDiag (rows: int) (cols: int) (f: int -> float) =
+        let A = SparseMatrix(rows,cols)
+        for i=0 to min (rows-1) (cols-1) do A.At(i,i,f i)
+        A :> _ Matrix
+
+    /// Create an identity matrix with the given dimension.
+    let inline identity (rows: int) (cols: int) = createDiag rows cols 1.0
+
+
     /// Create a matrix from a 2D array of floating point numbers.
     let inline ofArray2 array = SparseMatrix.OfArray(array) :> _ Matrix
 
@@ -166,33 +194,33 @@ module SparseMatrix =
     [<System.ObsoleteAttribute("Use ofListi instead. Will be changed to expect a non-indexed list in a future version.")>]
     let inline ofList (rows: int) (cols: int) (fl: list<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, Seq.ofList fl) :> _ Matrix
 
-    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
-    let inline ofRows (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfRowsCovariant(rows, cols, fss) :> _ Matrix
+
+    /// Create a matrix from a list of row vectors.
+    let inline ofRows (vectors: #Vector<float> list) = SparseMatrix.OfRowVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
-    let inline ofRowsList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfRowsCovariant(rows, cols, fll) :> _ Matrix
+    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfRowsCovariant(rows, cols, fll) :> _ Matrix
 
-    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
-    let inline ofColumns (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfColumnsCovariant(rows, cols, fss) :> _ Matrix
+    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
+    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfRowsCovariant(rows, cols, fss) :> _ Matrix
+
+    /// Create a matrix from a list of column vectors.
+    let inline ofColumns (vectors: #Vector<float> list) = SparseMatrix.OfColumnVectors(vectors |> Array.ofList |> box |> unbox) :> _ Matrix
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a column.
-    let inline ofColumnsList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfColumnsCovariant(rows, cols, fll) :> _ Matrix
+    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfColumnsCovariant(rows, cols, fll) :> _ Matrix
 
-    /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
-    let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, fs) :> _ Matrix
+    /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
+    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfColumnsCovariant(rows, cols, fss) :> _ Matrix
 
     /// Create a matrix with a given dimension from an indexed list of row, column, value tuples.
     let inline ofListi (rows: int) (cols: int) (fl: list<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, Seq.ofList fl) :> _ Matrix
 
-    /// Create a square matrix with constant diagonal entries.
-    let inline constDiag (n: int) (f: float) =
-        let A = SparseMatrix(n,n)
-        for i=0 to n-1 do
-            A.At(i,i,f)
-        A :> _ Matrix
+    /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
+    let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, fs) :> _ Matrix
 
     /// Create a square matrix with the vector elements on the diagonal.
-    let inline diag (v: #Vector<float>) =
+    let inline ofDiag (v: #Vector<float>) =
         let n = v.Count
         let A = SparseMatrix(n,n)
         A.SetDiagonal(v)
diff --git a/src/FSharp/LinearAlgebra.Double.Vector.fs b/src/FSharp/LinearAlgebra.Double.Vector.fs
index a6d6b7b3..202c4b8c 100644
--- a/src/FSharp/LinearAlgebra.Double.Vector.fs
+++ b/src/FSharp/LinearAlgebra.Double.Vector.fs
@@ -36,6 +36,8 @@ open MathNet.Numerics.LinearAlgebra
 [<CompilationRepresentation(CompilationRepresentationFlags.ModuleSuffix)>]
 module Vector =
 
+    // TODO: generalize or reconsider
+
     /// Creates a new vector and inserts the given value at the given index.
     let inline insert index value (v: #Vector<float>) =
         let newV = new DenseVector(v.Count + 1)
@@ -77,17 +79,12 @@ module DenseVector =
     /// Create a vector with a given dimension from an indexed sequences of index, value pairs.
     let inline ofSeqi (n: int) (fs: #seq<int * float>) = DenseVector.OfIndexedEnumerable(n, fs) :> _ Vector
 
+    /// Create a vector with integer entries in the given range.
+    let inline range (start: int) (step: int) (stop: int) = raw [| for i in start..step..stop -> float i |]
+
     /// Create a vector with evenly spaced entries: e.g. rangef -1.0 0.5 1.0 = [-1.0 -0.5 0.0 0.5 1.0]
-    let inline rangef (start: float) (step: float) (stop: float) =
-        let n = (int ((stop - start) / step)) + 1
-        let v = DenseVector(n)
-        for i=0 to n-1 do
-            v.At(i, (float i) * step + start)
-        v :> _ Vector
+    let inline rangef (start: float) (step: float) (stop: float) = raw [| start..step..stop |]
 
-    /// Create a vector with integer entries in the given range.
-    let inline range (start: int) (stop: int) =
-        DenseVector([| for i in [start .. stop] -> float i |]) :> _ Vector
 
 /// A module which implements functional sparse vector operations.
 [<CompilationRepresentation(CompilationRepresentationFlags.ModuleSuffix)>]
diff --git a/src/FSharpExamples/Matrices.fsx b/src/FSharpExamples/Matrices.fsx
index a465d04f..8dec98b1 100644
--- a/src/FSharpExamples/Matrices.fsx
+++ b/src/FSharpExamples/Matrices.fsx
@@ -53,16 +53,20 @@ let d1 = DenseMatrix.init 3 4 (fun i j -> float i / 100.0 + float j)
 let d2 = SparseMatrix.init 3 4 (fun i j -> if i=j then float i / 100.0 + float j else 0.0)
 
 // Matrices can also be constructed from sequences of rows or of columns
-let e1 = DenseMatrix.ofRows 20 10 (seq { for i in 1 .. 20 do yield Array.init 10 (fun j -> float j + 100.0 * float i) })
-let e2 = SparseMatrix.ofRows 20 10 (seq { for i in 1 .. 20 do yield Array.init 10 (fun j -> if i%5 = 0 then float j + 100.0 * float i else 0.0) })
-let e3 = DenseMatrix.ofColumns 20 10 (seq { for j in 1 .. 10 do yield Array.init 20 (fun i -> float j + 100.0 * float i) })
-let e4 = SparseMatrix.ofColumns 20 10 (seq { for j in 1 .. 10 do yield Array.init 20 (fun i -> if i%5 = 0 then float j + 100.0 * float i else 0.0) })
+let e1 = DenseMatrix.ofRowSeq 20 10 (seq { for i in 1 .. 20 do yield Array.init 10 (fun j -> float j + 100.0 * float i) })
+let e2 = SparseMatrix.ofRowSeq 20 10 (seq { for i in 1 .. 20 do yield Array.init 10 (fun j -> if i%5 = 0 then float j + 100.0 * float i else 0.0) })
+let e3 = DenseMatrix.ofColumnSeq 20 10 (seq { for j in 1 .. 10 do yield Array.init 20 (fun i -> float j + 100.0 * float i) })
+let e4 = SparseMatrix.ofColumnSeq 20 10 (seq { for j in 1 .. 10 do yield Array.init 20 (fun i -> if i%5 = 0 then float j + 100.0 * float i else 0.0) })
 
 // Or from F# lists
-let f1 = DenseMatrix.ofRowsList 20 10 [ for i in 1 .. 20 -> List.init 10 (fun j -> float j + 100.0 * float i) ]
-let f2 = SparseMatrix.ofRowsList 20 10 [ for i in 1 .. 20 -> List.init 10 (fun j -> if i%5 = 0 then float j + 100.0 * float i else 0.0) ]
-let f3 = DenseMatrix.ofColumnsList 20 10 [ for j in 1 .. 10 -> List.init 20 (fun i -> float j + 100.0 * float i) ]
-let f4 = SparseMatrix.ofColumnsList 20 10 [ for j in 1 .. 10 -> List.init 20 (fun i -> if i%5 = 0 then float j + 100.0 * float i else 0.0) ]
+let f1 = DenseMatrix.ofRowList 20 10 [ for i in 1 .. 20 -> List.init 10 (fun j -> float j + 100.0 * float i) ]
+let f2 = SparseMatrix.ofRowList 20 10 [ for i in 1 .. 20 -> List.init 10 (fun j -> if i%5 = 0 then float j + 100.0 * float i else 0.0) ]
+let f3 = DenseMatrix.ofColumnList 20 10 [ for j in 1 .. 10 -> List.init 20 (fun i -> float j + 100.0 * float i) ]
+let f4 = SparseMatrix.ofColumnList 20 10 [ for j in 1 .. 10 -> List.init 20 (fun i -> if i%5 = 0 then float j + 100.0 * float i else 0.0) ]
+
+// Or from row or column vectors
+let m1 = DenseMatrix.ofRows [DenseVector.create 3 1.0; DenseVector.create 3 2.0]
+let m2 = DenseMatrix.ofColumns [DenseVector.create 3 1.0; DenseVector.create 3 2.0]
 
 // Or from indexed lists or sequences where all other values are zero (useful mostly for sparse data)
 let g1 = DenseMatrix.ofListi 20 10 [(4,3,20.0); (18,9,3.0); (2,1,100.0)]
diff --git a/src/FSharpUnitTests/DenseMatrixTests.fs b/src/FSharpUnitTests/DenseMatrixTests.fs
index b3eaf756..f27a5f33 100644
--- a/src/FSharpUnitTests/DenseMatrixTests.fs
+++ b/src/FSharpUnitTests/DenseMatrixTests.fs
@@ -53,28 +53,28 @@ module DenseMatrixTests =
         DenseMatrix.ofList [[0.3;0.3];[0.3;0.3];[0.3;0.3]] |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofRows`` () =
-        DenseMatrix.ofRows 3 2 (Seq.ofList [[0.3;0.3];[0.3;0.3];[0.3;0.3]]) |> should equal smallM
+    let ``DenseMatrix.ofRowSeq`` () =
+        DenseMatrix.ofRowSeq 3 2 (Seq.ofList [[0.3;0.3];[0.3;0.3];[0.3;0.3]]) |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofRowsList`` () =
-        DenseMatrix.ofRowsList 3 2 [[0.3;0.3];[0.3;0.3];[0.3;0.3]] |> should equal smallM
+    let ``DenseMatrix.ofRowList`` () =
+        DenseMatrix.ofRowList 3 2 [[0.3;0.3];[0.3;0.3];[0.3;0.3]] |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofRowVectors`` () =
-        DenseMatrix.ofRowVectors [vector [0.3;0.3]; vector [0.3;0.3]; vector [0.3;0.3]] |> should equal smallM
+    let ``DenseMatrix.ofRows`` () =
+        DenseMatrix.ofRows [vector [0.3;0.3]; vector [0.3;0.3]; vector [0.3;0.3]] |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofColumn`` () =
-        DenseMatrix.ofColumns 3 2 (Seq.ofList [[0.3;0.3;0.3];[0.3;0.3;0.3]]) |> should equal smallM
+    let ``DenseMatrix.ofColumnSeq`` () =
+        DenseMatrix.ofColumnSeq 3 2 (Seq.ofList [[0.3;0.3;0.3];[0.3;0.3;0.3]]) |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofColumnsList`` () =
-        DenseMatrix.ofColumnsList 3 2 [[0.3;0.3;0.3];[0.3;0.3;0.3]] |> should equal smallM
+    let ``DenseMatrix.ofColumnList`` () =
+        DenseMatrix.ofColumnList 3 2 [[0.3;0.3;0.3];[0.3;0.3;0.3]] |> should equal smallM
 
     [<Test>]
-    let ``DenseMatrix.ofColumnVectors`` () =
-        DenseMatrix.ofColumnVectors [vector [0.3;0.3;0.3]; vector [0.3;0.3;0.3]] |> should equal smallM
+    let ``DenseMatrix.ofColumns`` () =
+        DenseMatrix.ofColumns [vector [0.3;0.3;0.3]; vector [0.3;0.3;0.3]] |> should equal smallM
 
     [<Test>]
     let ``DenseMatrix.ofSeqi`` () =
@@ -87,17 +87,17 @@ module DenseMatrixTests =
         |> DenseMatrix.ofListi 100 120 |> should equal largeM
 
     [<Test>]
-    let ``DenseMatrix.constDiag`` () =
-        DenseMatrix.constDiag 100 2.0 |> should equal (2.0 * (DenseMatrix.Identity 100))
+    let ``DenseMatrix.createDiag`` () =
+        DenseMatrix.createDiag 100 100 2.0 |> should equal (2.0 * (DenseMatrix.Identity 100))
 
     [<Test>]
-    let ``DenseMatrix.diag`` () =
-        DenseMatrix.diag (DenseVector.Create(100, fun i -> 2.0)) |> should equal (2.0 * (DenseMatrix.Identity 100))
+    let ``DenseMatrix.ofDiag`` () =
+        DenseMatrix.ofDiag (DenseVector.Create(100, fun i -> 2.0)) |> should equal (2.0 * (DenseMatrix.Identity 100))
 
     [<Test>]
-    let ``DenseMatrix.init_row`` () =
+    let ``DenseMatrix.initRow`` () =
         DenseMatrix.initRow 100 120 (fun i -> (DenseVector.init 120 (fun j -> float i * 100.0 + float j))) |> should equal largeM
 
     [<Test>]
-    let ``DenseMatrix.init_col`` () =
+    let ``DenseMatrix.initCol`` () =
         DenseMatrix.initCol 100 120 (fun j -> (DenseVector.init 100 (fun i -> float i * 100.0 + float j))) |> should equal largeM
diff --git a/src/FSharpUnitTests/DenseVectorTests.fs b/src/FSharpUnitTests/DenseVectorTests.fs
index 87549ec3..b70788ec 100644
--- a/src/FSharpUnitTests/DenseVectorTests.fs
+++ b/src/FSharpUnitTests/DenseVectorTests.fs
@@ -57,4 +57,4 @@ module DenseVectorTests =
 
     [<Test>]
     let ``DenseVector.range`` () =
-        DenseVector.range 0 99 |> should equal (new DenseVector( [| for i in 0 .. 99 -> float i |] ) )
+        DenseVector.range 0 1 99 |> should equal (new DenseVector( [| for i in 0 .. 99 -> float i |] ) )
diff --git a/src/FSharpUnitTests/SparseMatrixTests.fs b/src/FSharpUnitTests/SparseMatrixTests.fs
index 57b94432..86e0fb79 100644
--- a/src/FSharpUnitTests/SparseMatrixTests.fs
+++ b/src/FSharpUnitTests/SparseMatrixTests.fs
@@ -25,20 +25,20 @@ module SparseMatrixTests =
         SparseMatrix.ofArray2 (Array2D.init 4 6 (fun i j -> if i = 1 && j = 2 then 1.0 else 0.0)) |> should equal smallM
 
     [<Test>]
-    let ``SparseMatrix.ofRows`` () =
-        SparseMatrix.ofRows 4 6 (Seq.ofList [[0.;0.;0.;0.;0.;0.];[0.;0.;1.;0.;0.;0.];[0.;0.;0.;0.;0.;0.];[0.;0.;0.;0.;0.;0.]]) |> should equal smallM
+    let ``SparseMatrix.ofRowSeq`` () =
+        SparseMatrix.ofRowSeq 4 6 (Seq.ofList [[0.;0.;0.;0.;0.;0.];[0.;0.;1.;0.;0.;0.];[0.;0.;0.;0.;0.;0.];[0.;0.;0.;0.;0.;0.]]) |> should equal smallM
 
     [<Test>]
-    let ``SparseMatrix.ofRowsList`` () =
-        SparseMatrix.ofRowsList 4 6 [[0.;0.;0.;0.;0.;0.];[0.;0.;1.;0.;0.;0.];[0.;0.;0.;0.;0.;0.];[0.;0.;0.;0.;0.;0.]] |> should equal smallM
+    let ``SparseMatrix.ofRowList`` () =
+        SparseMatrix.ofRowList 4 6 [[0.;0.;0.;0.;0.;0.];[0.;0.;1.;0.;0.;0.];[0.;0.;0.;0.;0.;0.];[0.;0.;0.;0.;0.;0.]] |> should equal smallM
 
     [<Test>]
-    let ``SparseMatrix.ofColumns`` () =
-        SparseMatrix.ofColumns 4 6 (Seq.ofList [[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;1.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.]]) |> should equal smallM
+    let ``SparseMatrix.ofColumnSeq`` () =
+        SparseMatrix.ofColumnSeq 4 6 (Seq.ofList [[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;1.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.]]) |> should equal smallM
 
     [<Test>]
     let ``SparseMatrix.ofColumnList`` () =
-        SparseMatrix.ofColumnsList 4 6 [[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;1.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.]] |> should equal smallM
+        SparseMatrix.ofColumnList 4 6 [[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;1.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.];[0.;0.;0.;0.]] |> should equal smallM
 
     [<Test>]
     let ``SparseMatrix.ofSeqi`` () =
@@ -50,11 +50,11 @@ module SparseMatrixTests =
 
     [<Test>]
     let ``SparseMatrix.constDiag`` () =
-        SparseMatrix.constDiag 100 2.0 |> should equal (2.0 * (SparseMatrix.Identity 100))
+        SparseMatrix.createDiag 100 100 2.0 |> should equal (2.0 * (SparseMatrix.Identity 100))
 
     [<Test>]
     let ``SparseMatrix.diag`` () =
-        SparseMatrix.diag (DenseVector.Create(100, fun i -> 2.0)) |> should equal (2.0 * (SparseMatrix.Identity 100))
+        SparseMatrix.ofDiag (DenseVector.Create(100, fun i -> 2.0)) |> should equal (2.0 * (SparseMatrix.Identity 100))
 
     [<Test>]
     let ``SparseMatrix.init_row`` () =
diff --git a/src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs b/src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs
index a2c2eab3..fc316714 100644
--- a/src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs
+++ b/src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs
@@ -162,6 +162,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
             return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfColumnEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given column vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnVectors(params Vector<Complex>[] columns)
+        {
+            var storage = new VectorStorage<Complex>[columns.Length];
+            for (int i = 0; i < columns.Length; i++)
+            {
+                storage[i] = columns[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfColumnVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
         /// Each enumerable in the master enumerable specifies a column.
@@ -186,6 +201,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
             return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfRowEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given row vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowVectors(params Vector<Complex>[] rows)
+        {
+            var storage = new VectorStorage<Complex>[rows.Length];
+            for (int i = 0; i < rows.Length; i++)
+            {
+                storage[i] = rows[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfRowVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
         /// Each enumerable in the master enumerable specifies a row.
diff --git a/src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs b/src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs
index 836a780a..9a62af35 100644
--- a/src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs
+++ b/src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs
@@ -157,6 +157,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
             return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfColumnEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given column vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnVectors(params Vector<Complex32>[] columns)
+        {
+            var storage = new VectorStorage<Complex32>[columns.Length];
+            for (int i = 0; i < columns.Length; i++)
+            {
+                storage[i] = columns[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfColumnVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
         /// Each enumerable in the master enumerable specifies a column.
@@ -181,6 +196,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
             return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfRowEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given row vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowVectors(params Vector<Complex32>[] rows)
+        {
+            var storage = new VectorStorage<Complex32>[rows.Length];
+            for (int i = 0; i < rows.Length; i++)
+            {
+                storage[i] = rows[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfRowVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
         /// Each enumerable in the master enumerable specifies a row.
diff --git a/src/Numerics/LinearAlgebra/Double/SparseMatrix.cs b/src/Numerics/LinearAlgebra/Double/SparseMatrix.cs
index 4de87a06..5e5a703e 100644
--- a/src/Numerics/LinearAlgebra/Double/SparseMatrix.cs
+++ b/src/Numerics/LinearAlgebra/Double/SparseMatrix.cs
@@ -155,6 +155,21 @@ namespace MathNet.Numerics.LinearAlgebra.Double
             return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfColumnEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given column vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnVectors(params Vector<double>[] columns)
+        {
+            var storage = new VectorStorage<double>[columns.Length];
+            for (int i = 0; i < columns.Length; i++)
+            {
+                storage[i] = columns[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfColumnVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
         /// Each enumerable in the master enumerable specifies a column.
@@ -179,6 +194,21 @@ namespace MathNet.Numerics.LinearAlgebra.Double
             return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfRowEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given row vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowVectors(params Vector<double>[] rows)
+        {
+            var storage = new VectorStorage<double>[rows.Length];
+            for (int i = 0; i < rows.Length; i++)
+            {
+                storage[i] = rows[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfRowVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
         /// Each enumerable in the master enumerable specifies a row.
diff --git a/src/Numerics/LinearAlgebra/Single/SparseMatrix.cs b/src/Numerics/LinearAlgebra/Single/SparseMatrix.cs
index 7c1546e1..0ce2ae3c 100644
--- a/src/Numerics/LinearAlgebra/Single/SparseMatrix.cs
+++ b/src/Numerics/LinearAlgebra/Single/SparseMatrix.cs
@@ -155,6 +155,21 @@ namespace MathNet.Numerics.LinearAlgebra.Single
             return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfColumnEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given column vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnVectors(params Vector<float>[] columns)
+        {
+            var storage = new VectorStorage<float>[columns.Length];
+            for (int i = 0; i < columns.Length; i++)
+            {
+                storage[i] = columns[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfColumnVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
         /// Each enumerable in the master enumerable specifies a column.
@@ -179,6 +194,21 @@ namespace MathNet.Numerics.LinearAlgebra.Single
             return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfRowEnumerables(rows, columns, data));
         }
 
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given row vectors.
+        /// This new matrix will be independent from the vectors.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowVectors(params Vector<float>[] rows)
+        {
+            var storage = new VectorStorage<float>[rows.Length];
+            for (int i = 0; i < rows.Length; i++)
+            {
+                storage[i] = rows[i].Storage;
+            }
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfRowVectors(storage));
+        }
+
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
         /// Each enumerable in the master enumerable specifies a row.
diff --git a/src/Numerics/LinearAlgebra/Storage/DenseColumnMajorMatrixStorage.cs b/src/Numerics/LinearAlgebra/Storage/DenseColumnMajorMatrixStorage.cs
index 995ee7f6..d9cb7b1d 100644
--- a/src/Numerics/LinearAlgebra/Storage/DenseColumnMajorMatrixStorage.cs
+++ b/src/Numerics/LinearAlgebra/Storage/DenseColumnMajorMatrixStorage.cs
@@ -138,43 +138,8 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             return storage;
         }
 
-        public static DenseColumnMajorMatrixStorage<T> OfIndexedEnumerable(int rows, int columns, IEnumerable<Tuple<int, int, T>> data)
-        {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
-
-            var array = new T[rows * columns];
-            foreach (var item in data)
-            {
-                array[(item.Item2 * rows) + item.Item1] = item.Item3;
-            }
-            return new DenseColumnMajorMatrixStorage<T>(rows, columns, array);
-        }
-
-        public static DenseColumnMajorMatrixStorage<T> OfColumnMajorEnumerable(int rows, int columns, IEnumerable<T> data)
-        {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
-
-            var arrayData = data as T[];
-            if (arrayData != null)
-            {
-                var copy = new T[arrayData.Length];
-                Array.Copy(arrayData, copy, arrayData.Length);
-                return new DenseColumnMajorMatrixStorage<T>(rows, columns, copy);
-            }
-
-            var array = System.Linq.Enumerable.ToArray(data);
-            return new DenseColumnMajorMatrixStorage<T>(rows, columns, array);
-        }
-
         public static DenseColumnMajorMatrixStorage<T> OfColumnVectors(VectorStorage<T>[] data)
         {
-            if (data == null) throw new ArgumentNullException("data");
             int columns = data.Length;
             int rows = data[0].Length;
             var array = new T[rows * columns];
@@ -189,7 +154,7 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
                 else
                 {
                     // FALL BACK
-                    int offset = j*rows;
+                    int offset = j * rows;
                     for (int i = 0; i < rows; i++)
                     {
                         array[offset + i] = column.At(i);
@@ -201,13 +166,12 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         public static DenseColumnMajorMatrixStorage<T> OfRowVectors(VectorStorage<T>[] data)
         {
-            if (data == null) throw new ArgumentNullException("data");
             int rows = data.Length;
             int columns = data[0].Length;
             var array = new T[rows * columns];
             for (int j = 0; j < columns; j++)
             {
-                int offset = j*rows;
+                int offset = j * rows;
                 for (int i = 0; i < rows; i++)
                 {
                     array[offset + i] = data[i].At(j);
@@ -216,11 +180,34 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             return new DenseColumnMajorMatrixStorage<T>(rows, columns, array);
         }
 
+        public static DenseColumnMajorMatrixStorage<T> OfIndexedEnumerable(int rows, int columns, IEnumerable<Tuple<int, int, T>> data)
+        {
+            var array = new T[rows * columns];
+            foreach (var item in data)
+            {
+                array[(item.Item2 * rows) + item.Item1] = item.Item3;
+            }
+            return new DenseColumnMajorMatrixStorage<T>(rows, columns, array);
+        }
+
+        public static DenseColumnMajorMatrixStorage<T> OfColumnMajorEnumerable(int rows, int columns, IEnumerable<T> data)
+        {
+            var arrayData = data as T[];
+            if (arrayData != null)
+            {
+                var copy = new T[arrayData.Length];
+                Array.Copy(arrayData, copy, arrayData.Length);
+                return new DenseColumnMajorMatrixStorage<T>(rows, columns, copy);
+            }
+
+            var array = System.Linq.Enumerable.ToArray(data);
+            return new DenseColumnMajorMatrixStorage<T>(rows, columns, array);
+        }
+
         public static DenseColumnMajorMatrixStorage<T> OfColumnEnumerables<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<T>
         {
-            if (data == null) throw new ArgumentNullException("data");
             var array = new T[rows*columns];
             using (var columnIterator = data.GetEnumerator())
             {
@@ -255,7 +242,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<T>
         {
-            if (data == null) throw new ArgumentNullException("data");
             var array = new T[rows*columns];
             using (var rowIterator = data.GetEnumerator())
             {
diff --git a/src/Numerics/LinearAlgebra/Storage/SparseCompressedRowMatrixStorage.cs b/src/Numerics/LinearAlgebra/Storage/SparseCompressedRowMatrixStorage.cs
index 1c1ffc86..7dfed791 100644
--- a/src/Numerics/LinearAlgebra/Storage/SparseCompressedRowMatrixStorage.cs
+++ b/src/Numerics/LinearAlgebra/Storage/SparseCompressedRowMatrixStorage.cs
@@ -31,6 +31,7 @@
 using System;
 using System.Collections.Generic;
 using System.Linq;
+using System.Security.Cryptography.X509Certificates;
 using MathNet.Numerics.Properties;
 
 namespace MathNet.Numerics.LinearAlgebra.Storage
@@ -373,11 +374,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         public static SparseCompressedRowMatrixStorage<T> OfArray(T[,] array)
         {
-            if (array == null)
-            {
-                throw new ArgumentNullException("array");
-            }
-
             var storage = new SparseCompressedRowMatrixStorage<T>(array.GetLength(0), array.GetLength(1));
             var rowPointers = storage.RowPointers;
             var columnIndices = new List<int>();
@@ -429,13 +425,65 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             return storage;
         }
 
-        public static SparseCompressedRowMatrixStorage<T> OfIndexedEnumerable(int rows, int columns, IEnumerable<Tuple<int, int, T>> data)
+        public static SparseCompressedRowMatrixStorage<T> OfRowVectors(VectorStorage<T>[] data)
         {
-            if (data == null)
+            var storage = new SparseCompressedRowMatrixStorage<T>(data.Length, data[0].Length);
+            var rowPointers = storage.RowPointers;
+            var columnIndices = new List<int>();
+            var values = new List<T>();
+
+            // TODO PERF: Optimize for sparse and dense cases
+            for (int row = 0; row < storage.RowCount; row++)
             {
-                throw new ArgumentNullException("data");
+                var vector = data[row];
+                rowPointers[row] = values.Count;
+                for (int col = 0; col < storage.ColumnCount; col++)
+                {
+                    var x = vector.At(col);
+                    if (!Zero.Equals(x))
+                    {
+                        values.Add(x);
+                        columnIndices.Add(col);
+                    }
+                }
             }
 
+            storage.ColumnIndices = columnIndices.ToArray();
+            storage.Values = values.ToArray();
+            storage.ValueCount = values.Count;
+            return storage;
+        }
+
+        public static SparseCompressedRowMatrixStorage<T> OfColumnVectors(VectorStorage<T>[] data)
+        {
+            var storage = new SparseCompressedRowMatrixStorage<T>(data[0].Length, data.Length);
+            var rowPointers = storage.RowPointers;
+            var columnIndices = new List<int>();
+            var values = new List<T>();
+
+            // TODO PERF: Optimize for sparse and dense cases
+            for (int row = 0; row < storage.RowCount; row++)
+            {
+                rowPointers[row] = values.Count;
+                for (int col = 0; col < storage.ColumnCount; col++)
+                {
+                    var x = data[col].At(row);
+                    if (!Zero.Equals(x))
+                    {
+                        values.Add(x);
+                        columnIndices.Add(col);
+                    }
+                }
+            }
+
+            storage.ColumnIndices = columnIndices.ToArray();
+            storage.Values = values.ToArray();
+            storage.ValueCount = values.Count;
+            return storage;
+        }
+
+        public static SparseCompressedRowMatrixStorage<T> OfIndexedEnumerable(int rows, int columns, IEnumerable<Tuple<int, int, T>> data)
+        {
             var trows = new List<Tuple<int, T>>[rows];
             foreach (var item in data)
             {
@@ -478,8 +526,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<T>
         {
-            if (data == null) throw new ArgumentNullException("data");
-
             var storage = new SparseCompressedRowMatrixStorage<T>(rows, columns);
             var rowPointers = storage.RowPointers;
             var columnIndices = new List<int>();
@@ -517,8 +563,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<T>
         {
-            if (data == null) throw new ArgumentNullException("data");
-
             var trows = new List<Tuple<int, T>>[rows];
             using (var columnIterator = data.GetEnumerator())
             {
@@ -570,11 +614,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         public static SparseCompressedRowMatrixStorage<T> OfRowMajorEnumerable(int rows, int columns, IEnumerable<T> data)
         {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
-
             var storage = new SparseCompressedRowMatrixStorage<T>(rows, columns);
             var rowPointers = storage.RowPointers;
             var columnIndices = new List<int>();
@@ -605,10 +644,6 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         public static SparseCompressedRowMatrixStorage<T> OfColumnMajorList(int rows, int columns, IList<T> data)
         {
-            if (data == null)
-            {
-                throw new ArgumentNullException("data");
-            }
             if (rows * columns != data.Count)
             {
                 throw new ArgumentOutOfRangeException(Resources.ArgumentMatrixDimensions);