<abstract xmlns="http://www.w3.org/1999/xhtml"> In this article there is proposed a new two-parametrical variant of the gravitational classification method. We use the general idea of objects' behavior in a gravity field. Classification depends on a test object's motion in a gravity field of training points. To solve this motion problem, we use a simulation method. This classifier is compared to the 1NN method, because our method tends towards it for some parameter values. Experimental results on different data sets demonstrate an improvement in efficiency and that this approach outperforms the 1NN method by providing a significant reduction in the mean classification error rate. </abstract>

Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614 Poznań, Poland

Faculty of Civil Engineering, Environmental and Geodetic Sciences, Koszalin University of Technology, Śniadeckich 2, 75-453 Koszalin, Poland

A variant of gravitational classification

<abstract xmlns="http://www.w3.org/1999/xhtml"> In this paper we apply a parametric semi-Markov process to model the dynamic evolution of HIV-1 infected patients. The seriousness of the infection is rendered by the CD4+ T-lymphocyte counts. For this purpose we introduce the main features of nonhomogeneous semi-Markov models. After determining the transition probabilities and the waiting time distributions in each state of the disease, we solve the evolution equations of the process in order to estimate the interval transition probabilities. These quantities appear to be of fundamental importance for clinical predictions. We also estimate the survival probabilities for HIV infected patients and compare them with respect to certain categories, such as gender, age group or type of antiretroviral therapy. Finally we attach a reward structure to the aforementioned semi-Markov processes in order to estimate clinical costs. For this purpose we generate random trajectories from the semi-Markov processes through Monte Carlo simulation. The proposed model is then applied to a large database provided by ISS (Istituto Superiore di Sanità, Rome, Italy), and all the quantities of interest are computed.</abstract>

Survival probabilities for HIV infected patients through semi-Markov processes

<abstract xmlns="http://www.w3.org/1999/xhtml"> Global annual average temperature (GAAT) is regarded as a precise indicator of the warming of the globe over the centuries, and its spectre is looming large with the passage of time and with the advancement of civilization. Global warming, caused by the accumulation of greenhouse gases in the atmosphere, has become the worst environmental threat to mankind. The phase 1981 to 2012 was the most crucial phase, and the impact of global warming in that phase indeed points to a disaster if not controlled now. Work on the building of appropriate models to represent the GAAT data can be found in the literature, although the precision levels (in terms of R2 values) of such models do not exceed 0.86. In this paper, six models are developed by using different combinations of mathematical functions. The developed models are superior to existing models in terms of their precision. In fact, to generate such models, extensive simulation work has been carried out not only with respect to the types of mathematical functions, but also with respect to the choices of initial values of the coefficients involved in each model. The models developed here have attained R2 values as high as 0.896.</abstract>

Former Dean, Post Graduate Studies and Professor of Agricultural Statistics, Bidhan Chandra Krishi Viswavidyalaya, Faculty of Agriculture, Mohanpur, Nadia, West Bengal, 741252, India

Uttar Banga Krishi Viswavidyalaya, Department of Agricultural Statistics, Pundibari, Coochbehar, West Bengal, 736165, India

Global annual average temperature – a precise modelling

<abstract xmlns="http://www.w3.org/1999/xhtml">As a result of intensive changes in plant production and of environmental changes in agrocenoses, certain agrophages, such as slugs, have in recent years been causing ever increasing amounts of damage to crops of agricultural, horticultural and orchard plants. As a result of the European Parliament and Council Directive adopted on 13 January 2009, the countries of Europe have been required to implement integrated plant protection. One of the principles of this protection is the implementation of strategies which minimize the use of chemical pesticides. Moreover, in accordance with decisions of the European Commission, many active substances have been or are to be withdrawn from the list of available pesticides. An example is metaldehyde, which is to be withdrawn from use in EU countries in the next few years (Commission Decision C/2008/7637 of 5 December 2008). It therefore becomes necessary to seek environmentally safe substances and to develop non-chemical methods for protecting plants against harmful slugs.An alternative to chemical molluscicides is the parasitic nematode Phasmarhabditis hermaphrodita. Studies have been made of the effectiveness of this biological method in combating Polish populations of the invasive slug species Arion lusitanicus. This was an incomplete multivariate study, i.e. not all variables could be observed for all treatments on all experimental units. Multivariate model of observations has been derived and a method of analysis has been described. The results of these studies provide a basis for the development of environmentally friendly methods of protecting plants against harmful slugs.</abstract>

Department of Mathematical and Statistical Methods, Poznan University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland

Institute of Plant Protection – NRI, W. Węgorka 20, 60-318 Poznań, Poland

Institute of Agricultural Engineering, Department of Applied IT, Poznan University of Life Sciences, Wojska Polskiego 50, 60-637 Poznań, Poland

Analysis of studies of the effectiveness of a biological method of protection for organic crops

<abstract xmlns="http://www.w3.org/1999/xhtml"> Kernel principal components (KPC) and kernel discriminant coordinates (KDC), which are the extensions of principal components and discriminant coordinates, respectively, from a linear domain to a nonlinear domain via the kernel trick, are two very popular nonlinear feature extraction methods. The kernel discriminant coordinates space has proven to be a very powerful space for pattern recognition. However, further study shows that there are still drawbacks in this method. To improve the performance of pattern recognition, we propose a new learning algorithm combining the advantages of KPC and KDC </abstract>

President Stanislaw Wojciechowski Higher Vocational State School in Kalisz, Institute of Management, Nowy Świat 4, 62-800 Kalisz, Poland

Adam Mickiewicz University, Faculty of Mathematics and Computer Science, Umultowska 87, 61-614 Poznań, Poland

A kernel-based learning algorithm combining kernel discriminant coordinates and kernel principal components

AHEAD OF PRINT

Volume 60 (2023): Issue 2 (December 2023)

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Volume 49 (2012): Issue 2 (December 2012)

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Biometrical Letters

 Biometrical Letters is the official journal of the Polish Biometric Society, founded in 1964, now published with the financial support of the Ministry of Science and Higher Education. The anonymous double-blind peer review by the two independent reviewers is applied to all the papers.  The purposes of Biometrical Letters are:   publishing papers dealing with various aspects of the analysis and interpretation of results from biometrical experiments, using mathematical and statistical methods;  promoting and extending the use of statistical and mathematical methods in the principal disciplines of life sciences by reporting on the development and application of these methods;  presenting statistical and mathematical tools useful in biometry. Methodological developments should be motivated by interesting problems from life sciences, applied or applicable;  publishing review papers and papers presenting practical use of various methods of data analysis and statistical inference.   The core of most Biometrical Letters articles is statistical inference that sets scientific or policy objectives, motivates methodological development and demonstrates the operation of new methods.  The paper should include a description of the biometrical problem and a section detailing the application of the new methodology.  The Journal welcomes the submission of manuscripts from bioscience, mathematical and statistical theory, biology, genetics, medical statistics, agriculture, forestry, ecology, environmental sciences, biometrics and clinical trials. Case studies and articles on the use and development of statistical software are also welcome.  Rejection Rate   20%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 