ЭБ Раздел: https://elib.bsu.by:443/handle/123456789/93210 2026-04-20T09:55:19Z Data Analysis Using R and a Graphical Interface https://elib.bsu.by:443/handle/123456789/93539 Заглавие документа: Data Analysis Using R and a Graphical Interface Авторы: Dutter, R. Аннотация: The computer program system R provides efficient analysis methods for almost any kind of applied problems in statistics and is running on many computer platforms. It is developed on a non-commercial basis and therefore for many practitioners hard to use, nevertheless widely known. 2007-01-01T00:00:00Z On Statistical Analysis of Markov Chains under Missing Values https://elib.bsu.by:443/handle/123456789/93536 Заглавие документа: On Statistical Analysis of Markov Chains under Missing Values Авторы: Yarmola, A. N.; Kharin, Yu. S. Аннотация: In this paper we proposed methods of statistical analysis of Markov chains with missing values in the case of unknown lags between observations. The problem of statistical estimation of lags is studied. 2007-01-01T00:00:00Z Complexity Metrics and Exploratory Analysis of DNA Sequences https://elib.bsu.by:443/handle/123456789/93535 Заглавие документа: Complexity Metrics and Exploratory Analysis of DNA Sequences Авторы: Rekasius, T. Аннотация: A new measure of the distance between nucleotide sequences and the efficient method for visualisation of nucleotide sequences have been proposed. It facilitates visualisation of a long DNA sequence via a compact and smooth picture of all oligonucleotides of length up to 10 in the sequence. 2007-01-01T00:00:00Z Model Testing for High-Dimensional Contingency Tables with Application in Genetics https://elib.bsu.by:443/handle/123456789/93533 Заглавие документа: Model Testing for High-Dimensional Contingency Tables with Application in Genetics Авторы: Radavicius, M.; Zidanaviciute, J. Аннотация: In the paper it is supposed that random sequences is a finite-order Markov chain. The analysis of high order interactions in such sequences leads to large and sparse contingency tables. A special data presentation form and data transformation via multidimensional scaling enables us to apply generalized logit model and reduce the problem to the fitting nonparametric multinomial logistic regression with a few quantitative variables. 2007-01-01T00:00:00Z