13 papers · ranked by Valyu relevance
Natchalee Srimaneekarn, Anthony Hayter, Wei Liu, Chanita Tantipoj
Multivariate analysis with binary response is extensively utilized in dental research due to variations in dichotomous outcomes. One of the analyses for binary response variable is binary logistic regression, which explores the associated factors and predicts the response probability of the binary variable. This…
Kyungmin Lim, Su-Young Kim
In the structural equation modeling framework, binary variable models are generally considered a special case of ordinal variable models, as both involve similar scale assignment processes. However, the scaling processes of the two model types differ, with these differences becoming increasingly pronounced in the…
András Telcs, Raúl Alcaraz
We develop a finite-resolution empirical framework for applying nonnegative Mages-Anastasiadi-Rohner partial information decomposition (MAR-PID) to continuous and non-binary discrete variables. The variables are represented by recursive quantile binarization. This provides a balanced binary-tree representation at each…
Maryam Sadiq, Nasser A. Alsadhan, Ramla Shah, Sidra Younas + 2 more
'Zahid Rasheed' 'Suyan Tian'] Variable selection methods are very popular, especially in the field of big data with large predictors. These procedures improve the accuracy and performance of the model by eliminating irrelevant and redundant variables. The main contribution of this study is to couple a logit model with…
Meng Ji, Wenxiu Xie, Riliu Huang, Xiaobo Qian + 1 more
We aimed to develop a quantitative instrument to assist with the automatic evaluation of the actionability of mental healthcare information. We collected and classified two large sets of mental health information from certified mental health websites: generic and patient-specific mental healthcare information. We…
Maryam Sadiq, Ramla Shah, Muhammad Farooq Umer
The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive re-weighted sampling(CARS) and logistic regression for binary…
Mark de Rooij, Lorenza Cotugno, Roberta Siciliano
In this paper, we propose the generalized mixed reduced rank regression method, GMR3 for short. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables. The predictor variables can be a mix of binary, nominal, ordinal and numeric variables. For dealing with the categorical predictors we…
Vita Ratnasari, Purhadi, Marisa Rifada, Andrea Tri Rian Dani
Logit regression (or logistic regression) is a statistical analysis of categorical data. The binary responses have two categories. We present the Bivariate Polynomial Binary Logit Regression (BPBLR), which extends logit regression by modeling two correlated binary response variables. This model uses a polynomial…
Grenville J. Croll, Boris Ryabko
The distribution of prime numbers has long been viewed as a balance between order and randomness. In this work, we investigate the relationship between entropy, periodicity, and primality through the computational framework of the binary derivative. We prove that periodic numbers are composite in all bases except for a…
Jorge A. Morgan-Benita, José M. Celaya-Padilla, Huizilopoztli Luna-García, Carlos E. Galván-Tejada + 7 more
'Huizilopoztli Luna-García' 'Carlos E. Galván-Tejada' 'Miguel Cruz' 'Jorge I. Galván-Tejada' 'Hamurabi Gamboa-Rosales' 'Ana G. Sánchez-Reyna' 'David Rondon' 'Klinge O. Villalba-Condori' 'Aw Tar-Choon'] Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases in the world and poses a significant…
Xiaowei Wu, Hongxiao Zhu
We propose a new approach to test associations between binary trees and covariates. In this approach, binary-tree structured data are treated as sample paths of binary fission Markov branching processes (bMBP). We propose a generalized linear regression model and developed inference procedures for association testing…
Kun Tu, Dariusz Puchala, Jun Chen, Sadaf Salehkalaibar
In this paper, we address the problem of m-gram entropy variable-to-variable coding, extending the classical Huffman algorithm to the case of coding m-element (i.e., m-grams) sequences of symbols taken from the stream of input data for $m>1$. We propose a procedure to enable the determination of the frequencies of the…
Ibragim E. Suleimenov, Yelizaveta S. Vitulyova, Sherniyaz B. Kabdushev, Akhat S. Bakirov
'Sherniyaz B. Kabdushev' 'Akhat S. Bakirov'] Multivalued logics are becoming one of the most important tools of information technology. They are in great demand for creation of artificial intelligence systems that are close to human intelligence, since the functioning of the latter cannot be reduced to the operations…