XploRe Package for the Popular Parametric and the Semiparametric Single Index Models

Akkuş, ÖZge
October 2011
Gazi University Journal of Science;2011, Vol. 24 Issue 4, p753
Academic Journal
This study introduces and shows the applicability of the XploRe commands of the parametric and the semiparametric single index models, which are two most popular alternatives of each other. The commands required for the estimation in all stages of the semiparametric estimation and the parametric logistic, probit and complementary log log regression models are introduced in detail. An artificial data set is used to demonstrate the applicability of the commands in practice. The major contribution of this study is that it enables researchers to obtain additional outputs in easier way that are not so easy to have in the standard statistical packages especially for the semiparametric models. Additionally, users could extend and adapt these commands in conjunction with the new developments in this area.


Related Articles

  • A NOTE ON TWO CURIOSITIES IN LINEAR REGRESSION. Poirier, Dale J. // American Economist;Spring78, Vol. 22 Issue 1, p77 

    Focuses on two relationships involving alternative estimators of beta in linear regression. Condition for the operationality of the linear estimator of beta with minimum mean square error; Approaches in dealing with unknown parameters.

  • HiCNorm: removing biases in Hi-C data via Poisson regression. Hu, Ming; Deng, Ke; Selvaraj, Siddarth; Qin, Zhaohui; Ren, Bing; Liu, Jun S. // Bioinformatics;Dec2012, Vol. 28 Issue 23, p3131 

    Summary: We propose a parametric model, HiCNorm, to remove systematic biases in the raw Hi-C contact maps, resulting in a simple, fast, yet accurate normalization procedure. Compared with the existing Hi-C normalization method developed by Yaffe and Tanay, HiCNorm has fewer parameters, runs...

  • Unbiased Quasi-regression*. Guijun Yang; Lu Lin; Runchu Zhang // Chinese Annals of Mathematics;Apr2007, Vol. 28 Issue 2, p177 

    Quasi-regression, motivated by the problems arising in the computer experiments, focuses mainly on speeding up evaluation. However, its theoretical properties are unexplored systemically. This paper shows that quasi-regression is unbiased, strong convergent and asymptotic normal for parameter...

  • Optimal use of two auxiliary variables in double sampling. Diana, Giancarlo; Tommasi, Chiara // Statistical Methods & Applications;2004, Vol. 13 Issue 3, p275 

    Double sampling scheme is used when cheap auxiliary variables may be measured to improve the estimation of a finite population parameter. Several estimators for population mean, ratio of means and variance are available, when two dependent samples are drawn. However, there are few proposals for...

  • An alternative stochastic restricted Liu estimator in linear regression. Hu Yang; Jianwen Xu // Statistical Papers;Jun2009, Vol. 50 Issue 3, p639 

    In this paper, we introduce an alternative stochastic restricted Liu estimator for the vector of parameters in a linear regression model when additional stochastic linear restrictions on the parameter vector are assumed to hold. The new estimator is a generalization of the ordinary mixed...

  • Asymptotically normal estimation in the linear-fractional regression problem with random errors in coefficients. Linke, Yu.; Sakhanenko, A. // Siberian Mathematical Journal;May2008, Vol. 49 Issue 3, p474 

    We consider the problem of estimating the unknown parameter of the one-dimensional analog of the Michaelis-Menten equation when the independent variables are measured with random errors. We study the behavior of the explicit estimates that we have found earlier in the case of known independent...

  • Robust Estimation Algorithm for Technological Parameters of Automotive Ignition Coil. Qisong Wang; Dan Liu; Yongping Zhao // International Journal of Digital Content Technology & its Applic;Dec2011, Vol. 5 Issue 12, p119 

    An Improved Robust Least Squares Support Vector Regression (IRLSSVR) based on IGGIII weight function is presented to solve the problem that the technological parameters estimated precision of automotive ignition coil are usually influenced by gross errors. By utilizing IGGIII weight function,...

  • Criteria for Unconstrained Global Optimization in Nonconvex Problems. Demidenko, Eugene // AIP Conference Proceedings;9/6/2007, Vol. 936 Issue 1, p147 

    We develop criteria for the existence and uniqueness of global minima of a continuous bounded function on a noncompact set. Special attention is given to the problem of parameter estimation via minimization of the sum of squares in nonlinear regression and maximum likelihood. Definitions of...

  • Strong Nonlinear Correlations, Conditional Entropy and Perfect Estimation. Jones, Christopher S.; Finn, John M.; Hengartner, Nicolas // AIP Conference Proceedings;11/13/2007, Vol. 954 Issue 1, p293 

    This paper deals with parameter estimation in which measurements subjected to highly correlated noise allow for very accurate estimation. For linear regression with normally distributed noise, this generically occurs when the noise becomes highly linearly correlated. For a linear model with...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics