I am solving an asset pricing equations via discretizing an underlying Markov process, X \in R^d, resulting in \tilde{X} \sim \Pi, where \Pi is a transition matrix whose rows sum to unity, and all entries in [0,1]. Let \delta \in R^d be a constant vector s.t. \eta_t := \exp \left(\delta X_t \right) …

Solving Ax = b s.t. x contains all positive values

jlchan May 19, 2023, 9:54pm 3

Non-negative least squares would probably help too. NNLS.jl or NonNegLeastSquares.jl would be good places to start

1 Like

Topic		Replies	Views
Solving Boundary Value Problems with Shooting() and DifferentialEquations.jl Performance diffeq , performance	0	1364	August 20, 2020
Solving linear system BC = X where B is a symmetric positive semi-definite matrix Performance linearalgebra , matrices , linearsolve	7	325	June 6, 2024
Underdetermined Linear System General Solution Numerics	7	2746	April 21, 2020
Inconsistency when solving system of SDE with diagonal noise Numerics sde , differentialequation	1	207	April 6, 2024
Problem with DifferentialEquations.jl New to Julia	3	94	March 20, 2025