Assume a linear regression forecasting model and build a model for each of the five games (five models in total) by using the forecasting module of the POM software.Īnswer the three discussion questions for the case study, except the part requiring you to justify the forecasting as linear regression would be used.Ĭase Studies Southwestern University: (C) * For this case study, you are required to build a forecasting model.
#Using pom qm to solve a least squares software#
Use the forecasting module that you opened in the POM-QM for Windows software to solve the case study on page 146 of the Heizer and Render (2011) textbook (Southwestern University).
U := a + length(a)*signValue(a(1))*unitVector(m) R has (sign: R -> Integer) => coerce(sign(r)$R)$R V:Vector(R) ^ n:NonNegativeInteger = map((vi:R):R +-> vi^n, v)$Vector(R) Polyfit: (Vector(R),Vector(R),NonNegativeInteger) -> Vector(R) Qr: Matrix(R) -> Record(q:Matrix(R),r:Matrix(R)) SolveUpperTriangular: (Matrix(R),Vector(R)) -> Vector(R) "^": (Vector(R),NonNegativeInteger) -> Vector(R) UnitVector: NonNegativeInteger -> Vector(R) TestPackage(R:Join(Field,RadicalCategory)): with The following provides a generic QR decomposition for arbitrary precision floats, double floats and exact calculations: Q := Transpose (Q1 ) * Transpose (Q2 ) * TransPose (Q3 ) Hall (n - 1 + row, n - 1 + col ) := H (row, col ) Ī : constant Real_Matrix ( 1. Hall : Real_Matrix := Identity (inmat'Length ( 1 ) ) Ĭol := col - Mag (col ) * eVect (col, n ) H : Real_Matrix := Identity (mat'Length ( 1 ) ) mat'Length ( 2 ) ) įunction H_n (inmat : Real_Matrix n : Integer )ĬolT : Real_Matrix ( 1. n loop mat (i, i ) := 1.0 end loop įunction Chop (mat : Real_Matrix n : Integer ) return Real_Matrix is n => ( others => 0.0 ) ) įor i in Integer range 1. 1 ) įunction Identity (n : Integer ) return Real_Matrix is Generic_Elementary_Functionsįunction eVect (col : Real_Matrix n : Integer ) return Real_Matrix is Sum : Real_Matrix := Transpose (mat ) * mat 1 ) įunction Mag (mat : Real_Matrix ) return Float is Put (mat (row, col ), Exp => 0, Aft => 4, Fore => 5 ) įunction GetCol (mat : Real_Matrix n : Integer ) return Real_Matrix isĬolumn : Real_Matrix (mat' Range ( 1 ), 1. Output matches that of Matlab solution, not tested with other matrices. 12.1 QR decomposition with Numeric.LinearAlgebra.11.1 Method of task description, library go.matrix.You are encouraged to solve this task according to the task description, using any language you may know.Īny rectangular m × n