Results 81 to 90 of about 16,222,653 (310)
Non-parametric Latent Modeling and Network Clustering [PDF]
, 2020 The paper exposes a non-parametric approach to latent and co-latent modeling of bivariate data, based upon alternating minimization of the Kullback-Leibler divergence (EM algorithm) for complete log-linear models. For categorical data, the iterative algorithm generates a soft clustering of both rows and columns of the contingency table.
openaire +2 more sources
Semi-parametric models for response times and response accuracy in computerized testing [PDF]
, 2012 In computer-administered tests, response times can be recorded conjointly with the corresponding responses. This broadens the scope of potential modeling approaches because response times can be analyzed in addition to analyzing the responses themselves.
Wang, Chun
core
FEBS Letters, EarlyView.Cancer progression is regulated by the dynamic matrix code of the tumor microenvironment, which influences cellular behavior and disease development. Importantly, matrix remodeling in three‐dimensional cancer models more accurately reflects in vivo conditions compared to conventional two‐dimensional systems.
Sylvia Mangani +3 more
wiley +1 more source
Revista Colombiana de Estadística, 2007 Our goal is to model, with forecasting aims, the daily electricity demand in a southeast colombian region through a non-parametric regression model implementation. We consider some “calendar variables” such as time of the day, day of the week, month, and
Barrientos Andrés Felipe +2 more
doaj
FEBS Letters, EarlyView.The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi +6 more
wiley +1 more source
Correlated Non-Parametric Latent Feature Models
CoRR, 2012 Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI2009)
Finale Doshi-Velez, Zoubin Ghahramani
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Non-parametric estimation of forecast distributions in non-linear, non-gaussian state space models
, 2017 Non-Gaussian time series variables are prevalent in the economic and finance spheres, with state space models often employed to analyze such variables and, ultimately, to produce forecasts.
Ng, Jason Wei Jian (3718801)
core +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
New Agricultural Tractor Manufacturer’s Suggested Retail Price (MSRP) Model in Europe
AgricultureResearch investigating models for assessing new tractor pricing is notably scarce, despite its fundamental importance in conducting comprehensive cost analyses.
Ivan Herranz-Matey, Luis Ruiz-Garcia
doaj +1 more source
A non-parametric hidden Markov model for climate state identification [PDF]
Hydrology and Earth System Sciences, 2003 Hidden Markov models (HMMs) can allow for the varying wet and dry cycles in the climate without the need to simulate supplementary climate variables. The fitting of a parametric HMM relies upon assumptions for the state conditional distributions.
M. F. Lambert +3 more
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