We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coefficients is known. In the case with a single instrument, there is a unique non-randomized unbiased estimator based on the reduced-form and first-stage regression estimates. For cases with multiple instruments we propose...

The use of type Ia supernovae (SNe Ia) as cosmological standard candles is fundamental in modern observational cosmology. In this letter, we derive a simple empirical photometric redshift estimator for SNe Ia using a training set of SNe Ia with multiband (griz) light-curves and spectroscopic redshifts obtained by the Supernova Legacy Survey (SNLS). This estimator is analytical and model-indepen...

This paper deals with the asymptotic distribution of Wishart matrix and its application to the estimation of the population matrix parameter when the population eigenvalues are block-wise infinitely dispersed. We show that the appropriately normalized eigenvectors and eigenvalues asymptotically generate two Wishart matrices and one normally distributed random matrix, which are mutually independ...

this article examines statistical inference for  where and are independent but not identically distributed pareto of the first kind (pareto (i)) random variables with same scale parameter but different shape parameters. the maximum likelihood, uniformly minimum variance unbiased and bayes estimators with gamma prior are used for this purpose. simulation studies which compare the estimators are ...

In this paper we propose a novel approach to estimating Multiple-Input-Multiple-Output (MIMO) channels in space-time coded systems. The channel is assumed to introduce dispersion in both the spatial and temporal dimensions. The channel estimator is obtained by applying the Maximum Likelihood principle not only over a known pilot sequence, as it is done in the classical Least-Squares approaches,...

The Spearman-Kärber method can be used to estimate the threshold value or difference limen in two-alternative forced-choice tasks. This method yields a simple estimator for the difference limen and its standard error, so that both can be calculated with a pocket calculator. In contrast to previous estimators, the present approach does not require any assumptions about the shape of the true unde...

‎Zero-inflated negative binomial model is an appropriate choice to count response variables with excessive zeros and over-dispersion simultaneously. ‎This paper addressed parameter estimation in the zero-inflated when there are many parameters, ‎so that some of them have not influence on variable. ‎We proposed based linear shrinkage, ‎pretest, ‎shrinkage pretest, ‎Stein-type, ‎and positive Stei...

The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data. However, it is known that multicollinearity negatively affects the variance of the maximum likelihood estimator (MLE) of the Poisson regressio...

We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast in elliptical models that is against both heavy tails high dimensions. prove convergence iterative part our algorithm demonstrate favorable performance wide range simulation scenarios. Finally, an empirical application demonstrates its state-of-the-art on real data.

Inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. In this paper, we derive the Horvitz-Thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. We then introduce an alternative unbiased estimator, corresponding to post-st...