Pliska Studia Mathematica Bulgarica

Volume 17, 2005

Proceedings of the XI International Summer Conference on Probability and Statistics and Seminar on Statistical Data Analysis, Sozopol, 2004

GUEST EDITOR: N.Yanev


Contents

  • ATANASOV, D. Study on Robustness of Correlated Frailty Model, pp. 5-12 pageref
  • BENCHETTAH A. Characterization of Schrödinger Processes with Unbounded Potentials, pp. 13-26 pageref
  • CHRISTOZOV, D., P. MATEEV Assessment of Information Asymmetry, pp. 27-38 pageref
  • DIAS, G., E. ALVES, C. NUNES Topic Segmentation: How Much Can We Do by Counting Worts and Sequences of Words, pp. 39-70 pageref
  • FURLAN, R., R. CORRADETTI Analysing Conjoint Analysis Data by a Random Coefficient Regression Model, pp. 71-84 pageref
  • GONZÁLEZ, M., R. MARTÍNEZ, M. MOTA. A Note on the Extinction Problem for Controlled Multitype Branching Processes, pp. 85-96 pageref
  • GREGORI, D., R. ROSATO, G. CICCONE, L. LUSA Parameterized Link Functions in Generalized Linear Random Effect Models: a Case Study on Breast Cancer Treatment, pp. 97-108 pageref
  • JACOB, C., N. LALAM, N. YANEV Statistical Inference for Processes Depending on Environments and Application in Regenerative Processes, pp. 109-136 pageref
  • KHARIN, YU. S., A. S. HURYN Sensitivity Analysis of the Risk of Forecasting for Autoregressive Time Series with Missing Values, pp. 137-146 pageref
  • MARTÍNEZ, R., M. SLAVTCHOVA-BOJKOVA Comparison between Numerical and Simulation Methods for Age-dependent Branching Models with Immigration, pp. 147-154 pageref
  • MOLINA, M., M. MOTA, A. RAMOS Nonparametric Estimation in the Class of Bisexual Processes with Population-Size Dependent Mating, pp. 155-170 pageref
  • MOUHOUBI, Z., D. AIISSANI Some Inequalities of the Uniform Ergodicity and Strong Stability of Homogeneous Markov Chains, pp. 171-186 pageref
  • NEYKOV, N., R. DIMOVA, P. NEYTCHEV Trimmed Likelihood Estimation of the Parameters of the Generalized Extreme Value Distributions: a Monte-Carlo Study, pp. 187-200 pageref
  • POPOVIĆ, B. C., V. S. STOJANOVIĆ Split-ARCH, pp. 201-220 pageref
  • PRODANOVA, K., I. STOINOV, D. TERZIISKI Logistic Regression in Modelling Data for CVC - Related Infection, pp. 221-228 pageref
  • RÖMISCH, U. Application of Statistical Experimental Design in Food Sciences, pp. 229-240 pageref
  • SANJARI FARSIPOUR, N. Modelling Covariates in Multipath Change, pp. 241-248 pageref
  • SHISHKOV, B., H. MATSUMOTO, N. SHINOHARA Probabilistic Approach to Design of Large Antenna Arrays, pp. 249-270 pageref
  • STOEV, S., M. S. TAQQU Weak Convergence to the Tangent Process of the Linear Multifractional Stable Motion, pp. 271-294 pageref
  • STOIMENOVA, V., N. YANEV Parametric Estimation in Branching Processes with an Increasing Random Number of Ancestors, pp. 295-312 pageref
  • TSVETANOVA, Y. Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data, pp. 313-322 pageref
  • VANDEV, D. Stochastic Optimization in Robust Statistic, pp. 323- 336 pageref
  • YANEVA, J., N. DASKALOVA, N. YANEV Statistical Analysis of Data on Linker Histones/DNA Interactions, pp. 337-348 pageref
  • MITOV, K. V. Extremes of Bivariate Geometric Variables with Application to Bisexual Branching Processes, pp. 349-362 pageref

 


A B S T R A C T S


Study on Robustness of Correlated Frailty Model

Dimitar Atanasov

Sofia University, Department of Mathematics and Informatics,
5 J. Boucher Str.1407 Sofia, Bulgaria,

email: datanasov@fmi.uni-sofia.bg

This study considers a robust properties of correlated frailty models. The dependence between related individuals must be considered in order to be studied the difference between the gene information and the environment as causes of death. To do that, one can introduce the frailty parameter Z, which can be decomposed as Z =Zg+Ze, where Zg represents the frailty, due to the gene information, and Ze represents the influence of the environment. Using the WLTE(k) one can obtain a robust maximum likelihood estimation of the unknown parameters of the model.

KEY WORDS: frailty models, robust maximum likelihood estimation.

AMS 2000 subject classification: 62J12


Characterization of Schrödinger Processes with Unbounded Potentials

A. Benchettah

Universitè d'Annaba,
Facultè des sciences,
Dèpartement de Mathèmatiques,
BP 12, Annaba 23000

email: abenchettah@hotmail.com

This work is concerned with a class of Schrödinger process with unbounded potentials : a variant of Jamison's theorem is given without the assumption of continuity and of everywhere strict positivity of q. It associates with Jamison's data (q, Pa, Pb), the Csiszar's projection  Q* of a reference measure R* on a set   E(Pa, Pb) of probability measures with marginals Pa, Pb. Existence of a solution to the corresponding Schrödinger's system, construction of the Schrödinger's bridge and variational characterisation of Schrödinger process are established.

KEY WORDS: Schrödinger process, minimum entropy distance, stochastic optimal control, Schrödinger's system, variational characterisation.

AMS 2000 subject classification: 49L20, 60J60, 93E20


Assessment of Information Asymmetry

D. Christozov, P. Mateev

D. Christozov, American University in Bulgaria, Blagoevgrad, 2700
P. Mateev, Institute of Mathematics and Informatics, Bulgarian Academy of Science, 8 G. Bonchev Str. Sofia 1113, Bulgaria
e-mail: dgc@aubg.bg, pmat@math.bas.bg

In the process of trading, the seller and buyer participate with different initial knowledge about the technical capabilities and about the expected use of the good. This two-side asymmetry affects the success of the negotiation in e -trading. This paper discusses one practical approach to assess information asymmetry and the role of warranty in seller-buyer communication relationship. The presented approach is illustrated with a survey experiment.



KEY WORDS: information asymmetry, warranty.

AMS 2000 subject classification: 62P20, 91B42.


Topic Segmentation: How Much Can We Do by Counting Worts and Sequences of Words

G. Dias, E. Alves and C. Nunes

Centre of Human Language Technology and Bioinformatics
University of Beira Interior, Portugal
email:ddg@di.ubi.pt, elsalves@zmail.pt, celia@mat.ubi.pt

In this paper, we present an innovative topic segmentation system based on a new informative similarity measure that takes into account word co-occurrence in order to avoid the accessibility to existing linguistic resources such as electronic dictionaries or lexico -semantic databases such as thesauri or ontology. Topic segmentation is the task of breaking documents into topically coherent multi-paragraph subparts. Topic segmentation has extensively been used in information retrieval and text summarization. In particular, our architecture proposes a language-independent topic segmentation system that solves three main problems evidenced by previous research: systems based uniquely on lexical repetition that show reliability problems, systems based on lexical cohesion using existing linguistic resources that are usually available only for dominating languages and as a consequence do not apply to less favored languages and finally systems that need previously existing harvesting training data. For that purpose, we only use statistics on words and sequences of words based on a set of texts. This solution provides a flexible solution that may narrow the gap between dominating languages and less favored languages thus allowing equivalent access to information. 


Analysing Conjoint Analysis Data by a Random Coefficient Regression Model

Roberto Furlan, Roberto Corradetti

R. Furlan, GfK Martin Hamblin, London, UK
R. Corradetti, University of Torino, Department of Statistics and Applied Mathematics
"Diego de Castro", Torino, Italy

email: roberto.furlan@libero.it   roberto.corradetti@unito.it

Since late 1960s conjoint analysis has been applied in estimating consumer preferences in marketing research.

KEY WORDS: conjoint analysis, random coefficient regression model, full factorial design, fractional factorial design, design matrix

AMS 2000 subject classification: 62J12, 62K15, 91B42, 62H99


A Note on the Extinction Problem for Controlled Multitype Branching Processes

Miguel González, Rodrigo Martínez, Manuel Mota

University of Extremadura, Faculty of Sciences,
Department of Mathematics, 06071 Badajoz, Spain

email: mvelasco@unex.es   rmartinez@unex.es   mota@unex.es

In this paper we consider a discrete time controlled multitype branching process with random control in discrete time. We provide sufficient conditions for the almost sure extinction of the process as well as for its indefinite growth with a positive probability. Moreover an illustrative example is shown and some simulations are given.

KEY WORDS: controlled multitype branching processes, random control, homogeneous mutitype Markov chains.

AMS 2000 subject classification: 60J80, 60J10


Parameterized Link Functions in Generalized Linear Random Effect Models: a Case Study on Breast Cancer Treatment

Dario Gregori, Rosalba Rosato, Giovannino Ciccone, Lara Lusa

D. Gregori, University of Torino, Dept. of Public Health and Microbiology, Italy
R. Rosato and G. Ciccone, San Giovanni Battista Hospital, Unit of Tumor Epidemiology, Torino, Italy,
L. Lusa, National Institute of Cancer, Milano, Italy

email: 

In non-linear random effects some attention has been very recently devoted to the analysis ofsuitable transformation of the response variables separately (Taylor 1996) or not (Oberg and Davidian 2000) from the transformations of the covariates and, as far as we know, no investigation has been carried out on the choice of link function in such models. In our study we consider the use of a random effect model when a parameterized family of links (Aranda-Ordaz 1981, Prentice 1996, Pregibon 1980, Stukel 1988 and Czado 1997) is introduced. We point out the advantages and the drawbacks associated with the choice of this data-driven kind of modeling. Difficulties in the interpretation of regression parameters, and therefore in understanding the influence of covariates, as well as problems related to loss of efficiency of estimates and overfitting, are discussed. A case study on radiotherapy usage in breast cancer treatment is discussed.


Statistical Inference for Processes Depending on Environments and Application in Regenerative Processes

Christine Jacob, Nadia Lalam, Nicolas Yanev

Chr. Jacob, Applied Mathematics and Informatics unity, INRA,
78352 Jouy-en-Josas Cedex, France
N. Lalam, EURANDOM, P.O.Box 513, 5600 MB Eindhoven, The Netherlands
Nickolay Yanev, Institute of Mathematics and Informatics, BAS,
Acad. G. Bontchev Str. 1113 Sofia, Bulgaria

email: cj@banian.jouy.inra.fr   yanev@math.bas.bg

We consider a process {Zn}{n in N}, recursively defined by Zn = f(Fn-1,En) + h n, where Fn-1={Zk}k £ n-1, E{n}={Ck}k£ n, {Cn}n is an observed exogenous process and {h n}n is a martingale difference sequence for the filtration generated by (Fn-1, En) such that Var(h n|Fn-1,En)g(Fn-1,En) < ¥ , a.s. for some known function {g(Fn-1,En)}n. This class of models covers a very broad range of models such as regression models, ANOVA models, autoregressive processes, branching processes, regenerative processes, ... We assume that f(Fn-1,En) depends on an unknown parameter m 0 and that by notation f(.)= fm0(.) may be decomposed according to fm0(.)=f(1)q0(.) + f(2)m0(.), where q 0 in R d, dz < ¥ , is asymptotically identifiable in f(1)q0(.) as n ® ¥ at some rate v(.) whereas f(2)m0(.)v(.) is asymptotically negligible. We build the Conditional Least Squares Estimator of q 0 based on the observation of a single trajectory of {Zk,Ck}k, and give conditions ensuring its strong consistency. The particular case of general linear models according to m 0=(q0,n0) and among them, regenerative processes, are studied more particularly. In this frame, we may also prove the consistency of the estimator of n 0 although it belongs to an asymptotic negligible part of the model, and the asymptotic law of the estimator may also be calculated.


Sensitivity Analysis of the Risk of Forecasting for Autoregressive Time Series with Missing Values

Yu. S. Kharin, A. S. Huryn

Dept. of Mathematical Modeling and Data Analysis, Belarusian State University
Fr. Skoriny av. 4, 220050 Minsk, Belarus

email: kharin@bsu.by   hurynaliaksandr@yahoo.com

The problems of statistical forecasting of vector autoregressive time series with missing values are considered for different levels of prior information on the parameters of the underlying model. The mean square risk of forecasting and the risk sensitivity coefficient are evaluated and analyzed. Results of numerical experiments are presented.

KEY WORDS: forecasting, autoregression, missing values, risk, sensitivity

AMS 2000 subject classification: 62M20, 62M10, 62-07


Comparison between Numerical and Simulation Methods for Age-dependent Branching Models with Immigration

R. Martínez, M. Slavtchova-Bojkova

R. Martínez, University of Extremadura, Faculty of Sciences,
Department of Mathematics, 06071 Badajoz, Spain,
M. Slavtchova-Bojkova, Sofia University, 1164 Sofia and IMI, BAS, 1113 Sofia, Bulgaria

email: rmartinez@unex.es   bojkova@math.bas.bg

This work aims to provide and to compare numerical computation and simulation method to estimate the distribution of some relevant variables related to an age-dependent model allowing immigration at state zero. Specifically, we analyze the behaviour of the following variables: the extinction time and the waiting time for the beginning of the survival of population forever. They are strongly related to the population and re-population experiments in biology and to the wastewater treatment, as well. Throughout the paper, we illustrate the methods provided by some proper examples.

KEY WORDS: age-dependent branching processes with immigration at zero state, numerical computations, Monte-Carlo method

AMS 2000 subject classification: 60J80, 60J85


Nonparametric Estimation in the Class of Bisexual Processes with Population-Size Dependent Mating

Manuel Molina, Manuel Mota, Alfonso Ramos

University of Extremadura, Faculty of Sciences,
Department of Mathematics, 06071 Badajoz, Spain

email: mmolina@unex.es   mota@unex.es   aramos@unex.es

In this paper the class of bisexual branching processes with population-size dependent mating is considered. Nonparametric estimators and confidence intervals for the main parameters involved in such a class of stochastic models are provided. For the proposed estimators, the main conditional to non-extinction and conditional moments are established and some asymptotic properties are investigated. As illustration, a simulated example is given.

KEY WORDS: bisexual branching processes, population-size dependent processes, nonparametric inference, asymptotic properties.

AMS 2000 subject classification: 60J80, 62M05


Some Inequalities of the Uniform Ergodicity and Strong Stability of Homogeneous Markov Chains

Zahir Mouhoubi, Djamil Aiissani

L.A.M.O.S., Faculty of Sciences and Engineer Sciences
University of Bejaiia, 06000, Algeria

email: z_mouhoubi@yahoo.fr

In this paper we have established some uniform and strong stability estimates for homogeneous Markov chains under mixing conditions. As a general rule, the initial parameters values of the most complex systems has approximately known (they are defined on basis statistics methods), which involve errors for the calculus of research characteristics for each studied system. For this, the stability inequalities obtained in this paper allow us to use them in order to estimate numerically the error of definition for concerned characteristics, for a small perturbations of system's parameters. As an example of application, we are interesting about the well known waiting process where we consider the perturbation for the characteristics of the system when we apply a small perturbation for the control sequence.

KEY WORDS: quantitative estimates, uniform ergodicity, stability, strong stability, perturbation.

AMS 2000 subject classification: 60J45, 60K25


Trimmed Likelihood Estimation of the Parameters of the Generalized Extreme Value Distributions: a Monte-Carlo Study

Neyko Neykov, Rositsa Dimova, Plamen Neytchev

N. Neykov, P. Neytchev, National Institute of Meteorology and Hydrology, BAS,
66 Tsarigradsko chaussee, 1784 Sofia, Bulgaria
R. Dimova, Sofia university

email: neyko.neykov@meteo.bg   plamen.neytchev@meteo.bg   rdimova@fmi.uni-sofia.bg

The applicability of the Trimmed Likelihood Estimator (TLE) proposed by Neykov and Neytchev to the extreme value distributions is considered. The effectiveness of the TLE in comparison with the classical MLE in the presence of outliers in various scenarios is illustrated by an extended simulation study. The FAST-TLE algorithm developed by Neykov Müuller is used to get the parameter estimate. The computations are carried out in the R environment using the packages ismev originally developed by Coles and ported in R by Stephenson.

References

[1] Neykov N.M., P.N. Neytchev, A robust alternative of the maximum likelihood estimator. In Short communications of COMPSTAT'90, Dubrovnik, 1990, 99--100.

[2] Neykov, N. M., Ch. Müller, Breakdown point and computation of trimmed likelihood estimators in generalized linear models. In R. Dutter et al., editors, Developments in Robust Statistics Physica-Verlag, Heidelberg, 2002, 277--286.

[3] Coles, S.G. An introduction to statistical modeling of extreme values. Springer-Verlag, London, 2001.

[4] Stephenson, A.G. EVD: Extreme Value Distributions. R-News 2 (2002), 31--32. URL http://CRAN.R-project.org/doc/Rnews/

KEY WORDS: generalized extreme value distribution, maximum likelihood estimation, trimmed likelihood estimation, Monte-Carlo simulation.

AMS 2000 subject classification: 62F35, 62P99


Split-ARCH

Biljana Popović, Vladica Stojanović

B. Popovic, Dept. of Statistics, Faculty of Sciences and Mathematics,
18000 Niš, Višegradska 33, Serbia and Montenegro
V. Stojanovic, Faculty of Economics, Zubin Potok, Serbia and Montenegro

email: biljanap@junis.ni.ac.yu   vlada70@verat.net

We supplied the GARCH Zoo with the new model and introduce it in this paper. We named it Split-ARCH. It was empirically motivated by means of the real data set on soybean meal price on the Product exchange. Split-ARCH is the superstructure of the previously known models of GARCH type. We defined volatility exchange to follow sudden and great changes of the price, and volatility also. As far as the log returns of the price are defined as Xn=snen, we set the volatility to be
s n2=a0 +å pj=1 a j Xn-j2 +å qk=1 fk(sn-k2) I(e n-k2 >c ) n³ 0
with the threshold c>0. Under the stationarity conditions and specified f, we discus the possibilities of estimating parameters in this paper also.

KEY WORDS: conditional heteroscedasticity, conditional least squares.

AMS 2000 subject classification: 62M10


Logistic Regression in Modelling Data for CVC - Related Infection

Krasimira Prodanova, Ionko Stoinov, Dimitar Terziiski

K. Prodanova, I. Stoinov, Technical University of Sofia,
Faculty of Applied Mathematics and Informatics
D.Terziiski, Military Medical Academy,
Dept. of Anaesthesiology and Intensive Care Medicine, Sofia

email: kprod@tu-sofia.bg

A prospective study of all new central venous catheters (CVC) inserted for patients in intensive care unit in order to identify risk factors for CVC infection and to determine the rate of CVC related infection is undertaken. A catheter-related infection and sepsis was suspected in 62 cases of 118 CVC inserted in intensive care patients. A multiple logistic regression to obtain adjusted estimate of odds ratios and to identify which factors were associated independently with CVC related infection was performed. The variables which entered in the model were those found to be statistically significant (\alpha &le: 0.5) on univariate analysis and those which were established risk factors from previous research reports. The dependent variable was the CVC related infection. The independent variables were ten: age, sex, insertion site, number of lumens, duration of catheterization etc. The software package STATISTICA 6.0 was used for analyzing the real data.

KEY WORDS: Central Venious Catheter (CVC) infection, multinomial logistic regression

AMS 2000 subject classification: 62J12, 62P10


Application of Statistical Experimental Design in Food Sciences

Ute Römisch

TU, Berlin, Fac. of Process Sciences and Engeneering, Dept. of Informatics,
Gustav-Meyer-Allee 25, 13355 Berlin, Germany

email: ute.roemisch@tu-berlin.de

The development of new, health supporting food of high quality and the optimization of food technological processes today require the application of statistical methods of experimental design. The principles and steps of statistical planning and evaluation of experiments will be explained. By example of the development of a gluten-free rusk (zwieback), which is enriched by roughage compounds the application of a simplex-centroid mixture design will be shown. The results will be illustrated by different graphics.


Modelling Covariates in Multipath Change

N. Sanjari Farsipour

Dept. of Statistics, Shiraz University, Shiraz 71454, Iran
email: nsf@susc.ac.ir

In the multipath change - point problems, it is often of interest to assess the impact of covariates on the change point itself as well as on the parameter before and after the change point. In this paper, we consider a simple model for the change-point distribution, and then through hazard, we include covariates in the change point distribution. Maximum likelihood estimation is discussed.

KEY WORDS: covariate, maximum likelihood, modelling, multipath change-point problems.

AMS 2000 subject classification: 62N02


Probabilistic Approach to Design of Large Antenna Arrays

Blagovest Shishkov, Hiroshi Matsumoto, Naoki Shinohara

Blagovest Shishkov, Institute of Mathematics and informatics, BAS,
Dept. of Telecommunications, Acad. G. Bontchev Str., bl. 8, 1113 Sofia, Bulgaria
Hiroshi Matsumoto, Naoki Shinohara, Research Institute of Sustainable Humanspere,
Kyoto University, Uji, Japan

email: bshishkov@math.bas.bg   matsumot@rish.kyoto-u.ac.jp   shino@rish.kyoto-u.ac.jp

Recent advances in space exploration have shown a great need for antennas with high resolution, high gain and low sidelobe (SL) level. The last characteristic is of paramount importance especially for the Microwave Power Transmission (MPT) in order to achieve higher transmitting efficiency. In this concern statistical methods play an important role. Various probabilistic properties of a large antenna array with randomly, uniformly and combined spacing of elements are studied and especially the relationship between the required number of elements and their appropriate spacing from one part and the desired SL level, the aperture dimension, the beamwidth and transmitting efficiency from the other. We propose a new unified approach in searching for reducing SL level by exploiting the interaction of deterministic and stochastic workspaces of proposed algorithms, emphasizing on the distribution of the maximums of SL level. These models indicate any advantages with respect to sidelobes in the large area around the main beam. A new concept of designing a large antenna array system is proposed. Our theoretic study and simulation results clarify how to deal with the problems of sidelobes in designing a large antenna array, which seems to be an important step toward the realization of future SPS/MPT systems.

KEY WORDS: microwave power transmission, large antenna array, uniform spacing, random spacing, spatial and amplitude tapering, sidelobe level, grating lobes, workspace, transmitting efficiency.

AMS 2000 subject classification: 78A50


Weak Convergence to the Tangent Process of the Linear Multifractional Stable Motion

Stilian Stoev, Murad S. Taqqu

Boston University, Department of Mathematics,
111 Cummington St., Boston, MA 02215, USA

email: sstoev@bu.edu   murad@bu.edu

The linear multifractional stable motion (LMSM), Y={Y(t)}{t in R}, is an a-stable (0<a<2) stochastic process which exhibits local self-similarity. It is constructed by using a stochastic integral representation of the linear fractional stable motion (LFSM) process XH,a(t), where the self-similarity exponent H is replaced by a function H(t) in (0,1) of time t. Here, we focus on LMSM processes with continuous paths and study the convergence {1/d(l)(Y(lt + t0) - Y(t0))}t in [-1,1] Þ {Z(t)}t in [-1,1],   as ¯0, where Þ denotes the weak convergence of probability distributions on the space of continuous functions C[-1,1] equipped with the uniform norm and where d(l¯ 0. We show that if the function H(t) is sufficiently regular and if 1/a<H(t0)<1, then the above weak convergence holds with normalization d(l)=lH(t0) and the limit (tangent) process Z(t) is the LFSM XH(t0),a(t). We also show that one can have degenerate tangent processes Z(t), when the function H(t) is not sufficiently regular. The LMSM process is closely related to the Gaussian multifractional Brownian motion (MBM) process. We establish similar weak convergence results for the MBM.

KEY WORDS: path continuity, Hölder regularity, linear fractional stable motion, self-similarity, multifractional Brownian motion, local self-similarity, heavy tails.

AMS 2000 subject classification: 60G18, 60E07


Parametric Estimation in Branching Processes with an Increasing Random Number of Ancestors

Vessela Stoimenova, Nickolay Yanev

Vessela Stoimenova, Sofia University, Faculty of Mathematics and Informatics
5 J. Bourchier blvd, 1164 Sofia, Bulgaria
Nickolay Yanev, Institute of Mathematics and Informatics, BAS,
Acad. G. Bontchev Str. 1113 Sofia, Bulgaria

email: stoimenova@fmi.uni-sofia.bg   yanev@math.bas.bg

The paper deals with a parametric estimation in branching processes {Zt(n)} having random number of ancestors Z0(n) as both n and t tend to infinity (and thus Z0(n) in some sense). The offspring distribution is considered to belong to a discrete analogue of the exponential family - the class of the power series offspring distributions. Consistency and asymptotic normality of the estimators are obtained for all values of the offspring mean m, 0<m<¥, in the subcritical, critical and supercritical case.

KEY WORDS: branching processes, random number of ancestors, power series distribution, parametric estimation, consistency, asymptotic normality, efficiency.

AMS 2000 subject classification: 60J80, 62M05


Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

Yanka Tsvetanova

Trakia University, Faculty of Agriculture,
Dept. of Informatics, Mathematics and Physics, 6000 Stara Zagora

email: yanka@uni-sz.bg

Multivariate and univariate lactation models were applied to test day data to predict genetic value of daily milk yield of a sample of Black and White cows. The models for genetic evaluation include a set of fixed main effects, fixed regression on functions of days im milk, random effects of permanent environment within lactation, random additive genetic effect and residual effect. Under multivariate model for daily milk yield test day records within lactation are considered as repeated measurements, and different lactations are treated as separate traits. Univariate model is applied for each lactation using test day yield as repeated measure. The variance components, genetic parameters and ranging of the animals through the multivariate and univariate metod were compared.

KEY WORDS: mixed linear models, repeated measures, fixed regression, genetic parameters

AMS 2000 subject classification: 62H12, 62P99


Stochastic Optimization in Robust Statistic

D. Vandev

 

The paper studies a stochastic optimization algorithm for computing of robust estimators of location proposed by Vandev (1992). A random approximation of the exact solution was proposed which is much cheaper in time and easy to program. Two examples are presented. Besides standard estimators of location like trimmed mean also robust regressions (LMS and LTS) introduced by Rousseeuw and Leroy are considered. MATLAB programs are included.

KEY WORDS: robust estimators of location, least median of squares, stochastic approximation algotithm, Monte-Carlo study.

AMS 2000 subject classification: 62J05, 62G35


Statistical Analysis of Data on Linker Histones/DNA Interactions

J. Yaneva, N. Daskalova, N. Yanev

Julia Yaneva, Institute of Molecular Biology, BAS, Sofia, Bulgaria
Nina Daskalova, Nickolay Yanev, Institute of Mathematics and Informatics, BAS,
Acad. G. Bontchev Str. 1113 Sofia, Bulgaria

email: nina_rdm@yahoo.com   yanev@math.bas.bg

Linker histones (H1, H1o H5, subtypes and variants) play a pivotal role in formation of higher order chromatin structure and thus - as main regulators of the expression of genetic information kept in DNA. That is why the knowledge of the nature of linker histones/DNA interactions is of a greatest interest in understanding of such important issues as transcription regulation, cell division, and cancerogenesis. As DNA is a main "target" of most anticancer antibiotics, the analysis of competitive reactions between that drugs (in our case actinomycin D and netropsin) and linker histones for binding to certain sites in DNA gives hopeful information concerning the mode of such interactions. In this work we present statistical analysis of some experimental data concerning the influence of some anticancer antibiotics on linker histones/DNA interactions. First, it was investigated the formulated hypothesis of the dependence of H1/DNA interaction on actinomycin D concentration. Such a relation was expected knowing the different mode for binding of the both drugs to DNA double helix. The applied statistical analysis using chi-square test for independence showed that the concentration of Actinomycin D in reaction mixture had no essential effect on linker histone/DNA binding. On the contrary, the same analysis with the second antibiotic - netropsin showed that we could not reject the hypothesis of dependence. Some other statistical models are also proposed, applying chi-square test for homogeneity, test of Willcockson, Smirnov's test and others.

KEY WORDS: linker histones/DNA interactions, anticancer antibiotics, chi-square test.

AMS 2000 subject classification: 62P10, 92C40


Extremes of Bivariate Geometric Variables with Application to Bisexual Branching Processes

Kosto V. Mitov

National Military University "V. Levski"
Faculty of Aviation
5856 D. Mitropolia, Pleven, Bulgaria

email: kmitov@af-acad.bg

We obtain a limit theorem for the row maximum of a triangular array of bivariate geometric random vectors. An application of this limit theorem is provided for maximum family size within a generation of a bisexual branching process with varying geometric offspring laws.

KEY WORDS: bivariate geometric distributions, bisexual branching processes, varying environments, maximum family sizes.

AMS 2000 subject classification: 60J80, 60G70


 


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