We provide results on properties of the IV estimator in the presence of weak instruments, beginning with the derivation of analytical formulae for the asymptotic bias (ABIAS) and mean squared error (AMSE). We also obtain approximations for the ABIAS and AMSE formulae based on an asymptotic scheme; which, loosely speaking, requires the expectation of the first stage F-statistic to converge to a ...

We consider the problem of estimating density a random variable $X$ that can be sampled exactly by Monte Carlo (MC). investigate effectiveness replacing MC randomized quasi (RQMC) or stratified sampling over unit cube, to reduce integrated variance (IV) and mean square error (MISE) for kernel estimators. show theoretically empirically RQMC estimators achieve substantial reductions IV MISE, even...

We survey and compare a wide variety of techniques for estimating the condition number of a triangular matrix, and make recommendations concerning the use of the estimates in applications. Each of the methods is shown to bound the condition number; the bounds can broadly be categorised as upper bounds from matrix theory and lower bounds from heuristic or probabilistic algorithms. For each bound...

We develop results for the use of LASSO and Post-LASSO methods to form firststage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the sample size, n. We rigorously develop asymptotic distribution and inference theory for the resulting IV estimators and provide conditions under which th...

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990 s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression...

Atrial fibrillation (AF) may cause systolic abnormality via inadequate diastolic filling and tachycardia-induced cardiomyopathy. Global longitudinal strain (GLS) is a very sensitive method for detecting subtle left ventricular systolic dysfunction. Hence, this study aimed to evaluate whether AF patients had a more impaired GLS, AF was a major determinant of GLS, and determine the major correlat...

In random coefficients linear IV models, fixed effects averages of the individual-specific coefficients are biased in short panels due to the finite-sample bias of IV estimators. This paper introduces a new class of bias-corrected semiparametric estimators for panel models where the response to the regressors can be individual-specific in an unrestricted way. These estimators are based on momen...

Landsat remote sensing of the central African humid tropics is confounded by persistent cloud cover and, since 2003, missing data due to the Landsat-7 Enhanced Thematic Mapper Plus (ETM + ) scan line corrector (SLC) malfunction. To quantify these limitations and their effects on contemporary forest cover and change characterization, a comparison was made of multiple Landsat-7 image mosaics gene...

Abstract ? 1 -penalized quantile regression (QR) is widely used for analysing high-dimensional data with heterogeneity. It now recognized that the ?1-penalty introduces non-negligible estimation bias, while a proper use of concave regularization may lead to estimators refined convergence rates and oracle properties as signal strengthens. Although folded penalized M-estimation strongly convex lo...

BACKGROUND The Full Outline of UnResponsiveness (FOUR) has been proposed as an alternative for the Glasgow Coma Scale (GCS)/Glasgow Liège Scale (GLS) in the evaluation of consciousness in severely brain-damaged patients. We compared the FOUR and GLS/GCS in intensive care unit patients who were admitted in a comatose state. METHODS FOUR and GLS evaluations were performed in randomized order in...