Linear relationships

Relationships between Linear Dynamically Varying Systems and Jump Linear Systems

The connection between linear dynamically varying (LDV) systems and jump linear (JL) systems is explored. LDV systems have been used to model the error in nonlinear tracking problems. Some nonlinear systems, for example Axiom A systems, admit Markov partitions and their dynamics can be quantized as Markov chains. In this case the tracking error can be approximated by a JL system. It is shown th...

Estimation Of Multiple Linear Functional Relationships

Optimal Linear Estimation Fusion—Part V: Relationships

In this paper, we continue our study of optimal linear estimation fusion in a unified, general, and systematic setting. We clarify relationships among various BLUE and WLS fusion rules with complete, incomplete, and no prior information presented in Part I before; and we quantify the effect of prior information and data on fusion performance, including conditions under which prior information o...

Linear free energy relationships in halogen bonds 3

Four models of halogen bonds were used to quantify this bond using the DFT B97D/6-311+G(d) computational level: para-substituted iodobenzenes, paraand meta-substituted bromobenzenes complexed with three simple Lewis bases (NH3, NCH and CNH), 1-bromo-4-substituted-bicyclo[2.2.2]octanes with NH3 and 3and 4-substituted pyridines complexed with BrCl and BrF. In addition, the combination of the para...

strucchange: Testing for Structural Change in Linear Regression Relationships

i.e., that the regression coefficients remain constant, against the alternative that the coefficient vector varies over time. These tests can be divided in two classes, which are differently suitable for certain patterns of deviation from the null hypothesis. The first class are the tests from the generalized fluctuation test framework (Kuan and Hornik, 1995) that can detect various types of st...