High-Low and Least-Squares Methods
Total Least Squares Methods
... namely into scalar minimization problems, where each function evaluation requires the solution of a quadrat- ically constrained linear least squares problem. 26 The constrained formulation (10) has been ...
6
Overview of total least squares methods
... total least squares ...solution methods. In the case of the basic total least squares problem and the generalized total least squares problem, presented in Section ...
24
Least-Squares Methods for Policy Iteration
... reviews least- squares methods for policy iteration, an important class of algorithms for approxi- mate reinforcement ...called: least-squares temporal differ- ence, ...
38
Valuing American style derivatives by least squares methods
... Carlo methods with variance reduction techniques since, in this way, we can reduce the bias in the estimation of the early exercise value and achieve a more accurate price of the ...(2004b) methods to price ...
24
Valuing American Style Options by Least Squares Methods
... In the last few years, the LSM and the WME estimators have raised great interest amongst practitioners working in the finance industry. The main reason for this, as mentioned above, is their suitability for pricing very ...
18
Non-parametric and least squares Langley plot methods
... In most places where sun photometers are deployed, peri- ods of stable atmospheres are much less common, and they are frequently interrupted by cloud passages, changes in at- mospheric conditions like varying humidity ...
11
Numerical Analysis in Nonlinear Least Squares Methods and Applications
... usually high since it requires the expensive evaluation of ...numerical methods should merge with the Newtonβs method near the minimum point in order to achieve fast convergence rate ( Goh, 2009 ...
166
SELECTION OF REFERENCE PLANE BY THE LEAST SQUARES FITTING METHODS
... paper least square fitting methods (cylinder, polynomial) and commercial filters (Gaussian filter, Gaussian regression filter and ro- bust Gaussian regression filter) for areal form removal were compared ...
12
Regularization methods for the solution of a nonlinear least-squares problem in tomography
... 3.2.4 Comparisons between methods In this section we are going to compare the several methods we analysed and highlight pros and cons. From what we said in the previous sections, the Gauss-Newton method ...
104
Finite element least squares methods for a compressible stokes system
... KEEHWAN KIM, SANGDONG KIM, and SANGSIK SHIN Received 25 April 2002 The least-squares functional related to a vorticity variable or a velocity flux variable is consid- ered for two-dimensional compressible ...
10
Robust Least Squares Methods Under Bounded Data Uncertainties
... estimation methods and the direct LS estimation method tuned to the estimates of the data matrix and output ...estimation methods we propose can be cast as SDP problems, hence our methods can be ...
29
Numerical methods for least squares problems with application to data assimilation
... Probabilistic methods for 4DVAR problems (ensemble based methods) The aim of this chapter is to present the application of the approach developed in the previ- ous chapter to data assimilation problems ...
152
Numerical investigations of linear least squares methods for derivative estimation
... for least squares estimates of function gradients are ...a least squares problem using a truncated Taylor ...the least squares ...
14
Weighted least squares and adaptive least squares: further empirical evidence
... For instance, for specification S.1 with Ξ³ = 4 and n = 100, the average length of the ALS-HC confidence interval also amounts to only 18% of the average length of the OLS-HC confidence interval, while the empirical ...
36
The Method of Least Squares
... We can surmount this problem by taking a logarithmic transform of the data. Setting π¦ = log π, β± = log πΉ and β = log π, the relation πΉ = π/π π becomes β± = πβ + π¦. We are now in a situation where we can apply the Method ...
12
Experimental quality evaluation of lattice basis reduction methods for decorrelating low dimensional integer least squares problems
... integer least squares (ILS) estimate from noisy ...reduction methods for decorrelating ILS problems, including the LLL algorithm, its variant with deep insertions and our improved LLL algorithm with ...
29
Experimental quality evaluation of lattice basis reduction methods for decorrelating low-dimensional integer least squares problems
... The sorted QR ordering has been popular in com- munications and can be very effective in constructing a suboptimal integer estimator (see e.g., [24,25,46-48]). The terminology of sorted QR directly came from the publi- ...
30
High dimensional ordinary least squares projection for screening variables
... nine methods are shown in Table ...most methods work well for data sets with relatively simple structures, for example, the independent and autoregressive correlation structure; likewise, most of them fail ...
50
No penalty no tears : least squares in high dimensional linear models
... Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable for problems with dimensionality larger than the sample ...involving least squares fitting ...
27