An Exact Algorithm for Likelihood-Based Imprecise Regression in the Case of Simple Linear Regression with Interval Data
نویسندگان
چکیده
Likelihood-based Imprecise Regression (LIR) is a recently introduced approach to regression with imprecise data. Here we consider a robust regression method derived from the general LIR approach and we establish an exact algorithm to determine the set-valued result of the LIR analysis in the special case of simple linear regression with interval data.
منابع مشابه
On the implementation of LIR: the case of simple linear regression with interval data
This paper considers the problem of simple linear regression with intervalcensored data. That is, n pairs of intervals are observed instead of the n pairs of precise values for the two variables (dependent and independent). Each of these intervals is closed but possibly unbounded, and contains the corresponding (unobserved) value of the dependent or independent variable. The goal of the regress...
متن کاملRelation Between Imprecise DESA and MOLP Methods
It is generally accepted that Data Envelopment Analysis (DEA) is a method for indicating efficiency. The DEA method has many applications in the field of calculating the relative efficiency of Decision Making Units (DMU) in explicit input-output environments. Regarding imprecise data, several definitions of efficiency can be found. The aim of our work is showing an equivalence relation between ...
متن کاملSpatial Regression in the Presence of Misaligned data
In this paper, four approaches are presented to the problem of fitting a linear regression model in the presence of spatially misaligned data. These approaches are plug-in method, simulation, regression calibration and maximum likelihood. In the first two approaches, with modeling the correlation between the explanatory variable, prediction of explanatory variable is determined at sites...
متن کاملAn integrated heuristic method based on piecewise regression and cluster analysis for fluctuation data (A case study on health-care: Psoriasis patients)
Trend forecasting and proper understanding of the future changes is necessary for planning in health-care area.One of the problems of analytic methods is determination of the number and location of the breakpoints, especially for fluctuation data. In this area, few researches are published when number and location of the nodes are not specified.In this paper, a clustering-based method is develo...
متن کاملRobust regression with imprecise data
We consider the problem of regression analysis with imprecise data. By imprecise data we mean imprecise observations of precise quantities in the form of sets of values. In this paper, we explore a recently introduced likelihood-based approach to regression with such data. The approach is very general, since it covers all kinds of imprecise data (i.e. not only intervals) and it is not restricte...
متن کامل