Sökning: "Lagrange multiplier"
Visar resultat 1 - 5 av 14 avhandlingar innehållade orden Lagrange multiplier.
1. Likelihood-Based Panel Unit Root Tests for Factor Models
Sammanfattning : The thesis consists of four papers that address likelihood-based unit root tests for panel data with cross-sectional dependence arising from common factors.In the first three papers, we derive Lagrange multiplier (LM)-type tests for common and idiosyncratic unit roots in the exact factor models based on the likelihood function of the differenced data. LÄS MER
2. Likelihood-Based Tests for Common and Idiosyncratic Unit Roots in the Exact Factor Model
Sammanfattning : Dynamic panel data models are widely used by econometricians to study over time the economics of, for example, people, firms, regions, or countries, by pooling information over the cross-section. Though much of the panel research concerns inference in stationary models, macroeconomic data such as GDP, prices, and interest rates are typically trending over time and require in one way or another a nonstationary analysis. LÄS MER
3. Optimisation and control of boundary layer flows
Sammanfattning : Both optimal disturbances and optimal control are studied by means of numerical simulations for the case of the flat-plate boundary-layer flow. The optimisation method is the Lagrange multiplier technique where the objective function is the kinetic energy of the flow perturbations and the constraints involve the linearised Navier–Stokes equations. LÄS MER
4. Optimisation and control of shear flows
Sammanfattning : Transition to turbulence and flow control are studied by means of numerical simulations for different simple shear flows. Linear and non-linear optimisation methods using the Lagrange multiplier technique are employed. LÄS MER
5. Modelling and forecasting economic time series with single hidden-layer feedforward autoregressive artificial neural networks
Sammanfattning : This dissertation consists of 3 essays In the first essay, A Simple Variable Selection Technique for Nonlinear Models, written in cooperation with Timo Teräsvirta and Rolf Tschernig, I propose a variable selection method based on a polynomial expansion of the unknown regression function and an appropriate model selection criterion. The hypothesis of linearity is tested by a Lagrange multiplier test based on this polynomial expansion. LÄS MER