Estimation of parameters in a split functional model of geodetic observations (M split estimation)

Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model

Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...

On Optimal Data Split for Generalization Estimation and Model Selection

Modeling with flexible models, such as neural networks, requires careful control of the model complexity and generalization ability of the resulting model. Whereas general asymptotic estimators of generalization ability have been developed over recent years (e.g., [9]), it is widely acknowledged that in most modeling scenarios there isn't sufficient data available to reliably use these estimato...

Constrained Split Rate Estimation by Moving Horizon

The paper presents a method for the constrained Moving Horizon Estimation of origin-destination (OD) matrices for traffic networks. In traffic systems split ratios are important parameters for OD estimation and for control problems as well. The paper treats the general constrained Moving Horizon Estimation problem for traffic systems modelled in terms of linear time varying system and solves th...

Design and Estimation for Split Questionnaire Surveys

A KIND OF F-INVERSE SPLIT MODULES

Let M be a right module over a ring R. In this manuscript, we shall study on a special case of F-inverse split modules where F is a fully invariant submodule of M introduced in [12]. We say M is Z 2(M)-inverse split provided f^(-1)(Z2(M)) is a direct summand of M for each endomorphism f of M. We prove that M is Z2(M)-inverse split if and only if M is a direct...