It has been known since Phillips and Hansen (1990) that cointegrated systems can be consistently estimated using stochastic trend instruments that are independent of the system variables. A similar phenomenon occurs with deterministically trending instruments. The present work shows that such ‘‘irrelevant’’ deterministic trend instruments may be systematically used to produce asymptotically eff...

The paper is a contribution to parameter estimation in fuzzy regression models with random fuzzy sets. Here models with crisp parameters and fuzzy observations of the variables are investigated. This type of regressionmodelsmay be understood as an extension of the ordinary single equation linear regression models by integrating additionally the physical vagueness of the involved items. So the s...

We propose a method of least squares approximation (LSA) for unified yet simple LASSO estimation. Our general theoretical framework includes ordinary least squares, generalized linear models, quantile regression, and many others as special cases. Specifically, LSA can transfer many different types of LASSO objective functions into their asymptotically equivalent least-squares problems. Thereaft...

This paper demonstrates that the randomization-based “Neyman” and constanteffects estimators for the variance of estimated average treatment effects are equivalent to a variant of White’s “heteroskedasticity-robust” estimator and the homoskedastic ordinary least squares (OLS) estimator, respectively.

A parameter estimation problem for ellipsoid fitting in the presence of measurement errors is considered. The ordinary least squares estimator is inconsistent, and due to the nonlinearity of the model, the orthogonal regression estimator is inconsistent as well, i.e., these estimators do not converge to the true value of the parameters, as the sample size tends to infinity.A consistent estimato...

In general, the coefficient estimates of linear models are carried out using ordinary least squares (OLS) method. Since analysis variance is also a model, coefficients can be estimated least-squares this study, in two-way were performed by Cholesky decomposition. The purpose decomposition finding make variables used model being orthogonal such that important easily identified. sum (row, column,...

The goal of phylogenetic inference is the reconstruction of the evolutionary history of various biological entities (taxa) such as genes, proteins, viruses or species. Phylogenetic inference is of major importance in computational biology and has numerous applications ranging from the study of biodiversity to sequence analysis. Given a matrix of pairwise distances between taxa, the minimum evol...

With increasing liquidity of the Indian sovereign debt market since 1997, it has become possible to estimate the term structure in India. However, the market is characterised by several frictions that cause individual securities to be priced differently from the 'average' pricing in the market. In such a scenario, traditional estimation procedures like ordinary least squares using various funct...

The aim of this study is to determine the natural and anthropogenic factors affecting air quality index (AQI) create a model that shows effects these on AQI values in cities Turkey. Natural factors, which are thought have an effect AQI, were determined interpreted with kriging maps. examined by explanatory spatial data analysis (ESDA). Global Moran’s I local (LISA) indices for presence relation...