Towards Efficient Estimations of Parameters in Stochastic Differential Equations

Rune Juhl

AbstractStochastic differential equations are gaining popularity, but estimating the models can be rather time consuming. CTSM v2.3 is a graphical entry point which quickly becomes cumbersome. The present thesis successfully implements CTSM in the scriptable R language and exploit the independent function evaluations in the gradient.
Several non-linear model are tested to determine the performance running parallel. The best speed-up observed is 10x at a low cost of additional total CPU usage of a few percent.
The new CTSM interface lets a user diagnose erroneous estimations using the newly added traces of the Hessian, gradient and parameters. It lives within R and its very flexible environment where data preprocessing and post processing can be performed with the new CTSM.
TypeMaster's thesis [Academic thesis]
Year2011
PublisherTechnical University of Denmark, DTU Informatics, E-mail: reception@imm.dtu.dk
AddressAsmussens Alle, Building 305, DK-2800 Kgs. Lyngby, Denmark
SeriesIMM-M.Sc.-2011-89
NoteSupervised by Professor Henrik Madsen, hm@imm.dtu.dk, DTU Informatics
Electronic version(s)[pdf]
Publication linkhttp://www.imm.dtu.dk/English.aspx
BibTeX data [bibtex]
IMM Group(s)Mathematical Statistics