This paper considers estimation of the coe¢ cients in a semiparametric multinomial choice model with linear indirect utility functions (with common coe¢ cients but di¤ering regressors) and errors that are assumed to be independent of the regressors. This implies that the conditional mean of the vector of dependent indicator variables is a smooth and invertible function of a corresponding vector...

The usual standard errors for the regression coe cients in a Seemingly Unrelated Regression model have a substantial downward bias. Bootstrapping the standard errors does not seem to improve inferences. In this paper Monte Carlo evidence is reported which indicates that bootstrapping can result in substantially better inferences when applied to t-ratios rather than to standard errors. 3

In many multivariate statistical techniques, a set of linear functions of the original p variables is produced. One of the more difŽ cult aspects of these techniques is the interpretation of the linear functions, as these functions usually have nonzero coefŽ cients on all p variables. A common approach is to effectively ignore (treat as zero) any coefŽ cients less than some threshold value, so ...

ALLMAN MICHAL, ALLMANOVÁ ZUZANA, JANKOVSKÝ MARTIN, FERENČÍK MICHAL, MESSINGEROVÁ VALÉRIA. 2016. Damage of the Remaining Stands Caused by Various Types of Logging Technology. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(2): 379–385. Forest harvesting causes a lot of damage, which results in damage of the remaining stand. These damages have diff erent character. Thei...

We consider the problem of missing data when the mechanism of missingness is not at random and when the partially observed variable has known or observed moments. A nonparametric estimator of the probability of missingness is proposed. A data driven statistic is constructed to test the missingness mechanism. Illustrations through univariate logistic regressions are presented: the method permits...

This paper presents a fully Bayesian approach to regression splines with automatic knot selection in generalized semiparametric models for fundamentally non Gaussian responses In a basis function representation of the regression spline we use a B spline basis The reversible jump Markov chain Monte Carlo method allows for simultaneous estimation both of the number of knots and the knot placement...

This paper considers a nested error component model with unbalanced data and proposes simple analysis of variance (ANOVA), maximum likelihood (MLE) and minimum norm quadratic unbiased estimators (MINQUE)-type estimators of the variance components. These are natural extensions from the biometrics, statistics and econometrics literature. The performance of these estimators is investigated by mean...

in this paper, a new and ecient approach based on operational matrices with respect to the gener-alized laguerre polynomials for numerical approximation of the linear ordinary dierential equations(odes) with variable coecients is introduced. explicit formulae which express the generalized la-guerre expansion coecients for the moments of the derivatives of any dierentiable function in terms...

This paper derives the exact functional form of an error contaminated regression function when the error free regression is a polynomial function of error free covariates (discrete or continuous) which are contaminated by normally distributed measurement error, with coe¢cients which may be arbitrary functions of error free covariates. The form of higher order central moment error contaminated r...

VASILEVA, S. and M. MARCHEVA, 2016. Genetic analysis of productivity components in malting barley (Hordeum vulgare, L.) hybrid progenies. Bulg. J. Agric. Sci., 22: 452–457 The investigation was conducted on the experimental fi eld of the Agricultural University of Plovdiv, during the period 2011–2014. Coeffi cients of heritability and selection, the number of genes, transgressions and heterosis...