Estimation and hypothesis testing in BIB design and robustness

Tiku, Moti L.
Modified maximum likelihood estimators of the unknown parameters in a BIB design under non-normality of error distributions are obtained. They are shown to be more efficient and robust than the traditional least squares estimators. A test statistic for testing a linear contrast among treatment effects is developed. A real life example is given.


Estimation in bivariate nonnormal distributions with stochastic variance functions
Tiku, Moti L.; İslam, Muhammed Qamarul; SAZAK, HAKAN SAVAŞ (Elsevier BV, 2008-01-01)
Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distributions. Estimation of parameters in such situations is considered when the mean and variance of one variable is a linear and a positive function of the other variable. This is typically true of bivariate t distribution. The resulting estimators are found to be remarkably efficient. Hypothesis testing procedures are developed and shown to be robust and powerful. Real life examples are given.
Analysis of variance and linear contrasts in experimental design with generalized secant hyperbolic distribution
Yilmaz, Yidiz E.; Akkaya, Ayşen (Elsevier BV, 2008-07-01)
We consider one-way classification model in experimental design when the errors have generalized secant hyperbolic distribution. We obtain efficient and robust estimators for block effects by using the modified maximum likelihood estimation (MML) methodology. A test statistic analogous to the normal-theory F statistic is defined to test block effects. We also define a test statistic for testing linear contrasts. It is shown that test statistics based on MML estimators are efficient and robust. The methodolo...
Finite element error analysis of a variational multiscale method for the Navier-Stokes equations
Volker, John; Kaya Merdan, Songül (Springer Science and Business Media LLC, 2008-01-01)
The paper presents finite element error estimates of a variational multiscale method (VMS) for the incompressible Navier-Stokes equations. The constants in these estimates do not depend on the Reynolds number but on a reduced Reynolds number or on the mesh size of a coarse mesh.
Dynamic programming for a Markov-switching jump-diffusion
Azevedo, N.; Pinheiro, D.; Weber, Gerhard Wilhelm (Elsevier BV, 2014-09-01)
We consider an optimal control problem with a deterministic finite horizon and state variable dynamics given by a Markov-switching jump-diffusion stochastic differential equation. Our main results extend the dynamic programming technique to this larger family of stochastic optimal control problems. More specifically, we provide a detailed proof of Bellman's optimality principle (or dynamic programming principle) and obtain the corresponding Hamilton-Jacobi-Belman equation, which turns out to be a partial in...
Implicit motif distribution based hybrid computational kernel for sequence classification
Atalay, Mehmet Volkan (Oxford University Press (OUP), 2005-04-15)
Motivation: We designed a general computational kernel for classification problems that require specific motif extraction and search from sequences. Instead of searching for explicit motifs, our approach finds the distribution of implicit motifs and uses as a feature for classification. Implicit motif distribution approach may be used as modus operandi for bioinformatics problems that require specific motif extraction and search, which is otherwise computationally prohibitive.
Citation Formats
M. L. Tiku and B. ŞENOĞLU, “Estimation and hypothesis testing in BIB design and robustness,” COMPUTATIONAL STATISTICS & DATA ANALYSIS, pp. 3439–3451, 2009, Accessed: 00, 2020. [Online]. Available: