BiDimRegression: Bidimensional Regression Modeling UsingR

BiDimRegression: Bidimensional Regression Modeling Using R

Tobler (1965) introduced bidimensional regression to the research field of geography in 1965 to provide a method for estimating mapping relations between two planes on the basis of regression modeling. The bidimensional regression method has been widely used within geographical research. However, the applicability in assessing the degree of similarity of two-dimensional patterns has not much ex...

Bidimensional regression: Issues with Interpolation

We investigated the interpolation of missing values in data that were fit by bidimensional regression models. This addresses a problem in spatial cognition research in which sketch maps are used to assess the veracity of spatial representations. In several simulations, we compared samples of different sizes with different numbers of interpolated coordinate pairs. A genetic algorithm was used in...

Bayesian Bidimensional Regression and Its Extension

Reduction of Bidimensional Spectral

This paper presents an outline of the software, written by the author, for the reduction of bidimensional spectral data obtained with the Russian 6-meter telescope using the Multi-Pupil Field Spectrograph (MPFS). The MPFS uses diierent detectors, an IPCS and CCDs, in combination with a scanning Fabry-Perot interferometer, etc. The principal algorithms, concerning the basic reduction steps such ...

[Regression modeling strategies].

Multivariable regression models are widely used in health science research, mainly for two purposes: prediction and effect estimation. Various strategies have been recommended when building a regression model: a) use the right statistical method that matches the structure of the data; b) ensure an appropriate sample size by limiting the number of variables according to the number of events; c) ...