Results 91 to 100 of about 100,752 (312)

Estimating multinomial logit model with multicollinear data

, 2010
The multinomial logit model is used to study the dependence relationship between a categorical response variable with more than two categories and a set of explicative variables.
Lucadamo A., CAMMINATIELLO, Ida
core   +1 more source

Modeling repeated ordinal responses using a family of power transformations: application to neonatal hypothermia data

BMC Medical Research Methodology, 2005
Background For analyzing a repeated ordinal response, it is common to use a multivariate cumulative logit model. This model may fit poorly, especially when a nonsymmetric response is available.
Khanafshar Navid, Kazemnejad Anoshirvan, Zayeri Farid, Nayeri Fatemeh   +3 more
doaj   +1 more source

Bootstrapping Logit Model

Communications for Statistical Applications and Methods, 2002
In this paper, we considered an application of the bootstrap method for logit model. Estimation of type I error probability, the bootstrap p-values and bootstrap confidence intervals of parameter were proposed. Small sample Monte Carlo simulation were conducted in order to compare proposed method with existing normal theory based asymptotic method.
Dae-hak Kim, Hyeong-Chul Jeong
openaire   +2 more sources

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

TÜRKİYE’DE HANEHALKLARININ BALIK TÜKETİM HARCAMALARI: LOGIT VE MULTINOMIAL LOGIT YAKLAŞIMLARI

Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2020
Çalışmada insan sağlığı üzerinde kanıtlanmış olumlu etkileri olan balık tüketiminin Türkiye hanehalkları için belirleyicileri analiz edilmiştir. Bu amaçla Türkiye İstatistik Kurumu'nun 2018 yılı Hanehalkı Bütçe Araştırması Mikro Veri Setinde yer alan 11 ...
Onur Demirel, Selim Adem Hatırlı
doaj   +1 more source

Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays

Advanced Science, EarlyView.
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo, Ji‐Hwan Eum, Suk‐Jeong Kwon, Minji Sagong, Dongchan Kim, Dong‐Ha Kim   +5 more
wiley   +1 more source

Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels: A Finite Mixture Approach [PDF]

This paper proposes a new approach to dealing with unobserved heterogeneity in applied research using the binary logit model with cross-sectional data and short panels.
Anders Holm, Morten Pedersen, Mads Meier Jæger   +2 more
core  

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

Advanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

Results of the ordered logit model.

, 2016
Results of the ordered logit model.
Xiaonan Cai (754620), Chen Wang (88408), Shengdi Chen (406669), Jian Lu (51707)   +3 more
core   +1 more source

Comparing methods for risk prediction of multicategory outcomes: dichotomized logistic regression vs. multinomial logit regression

BMC Medical Research Methodology
Background Medical outcomes of interest to clinicians may have multiple categories. Researchers face several options for risk prediction of such outcomes, including dichotomized logistic regression and multinomial logit regression modeling.
Lei Li, Matthew A. Rysavy, Georgiy Bobashev, Abhik Das   +3 more
doaj   +1 more source