Results 81 to 90 of about 18,151,738 (262)
Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering [PDF]
This paper analyzes patterns in the earnings development of young labor market entrants over their life cycle. We identify four distinctly different types of transition patterns between discrete earnings states in a large administrative data set. Further,
Sylvia Frühwirth-Schnatter +3 more
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ESTIMATE OF TIME SERIES SIMILARITY BASED ON MODELS
Міжнародний науково-технічний журнал "Проблеми керування та інформатики"Determining the measure of the distance between time series is the starting point for many data mining tasks such as clustering and classification. Clustering is the main method of teaching without a teacher, which is used to divide data into groups ...
Т.В. Кнігніцька
doaj +1 more source
Similarity dynamical clustering algorithm based on multidimensional shape features for time series
工程科学学报, 2017 Traditional data mining methods are difficult to deal with the high dimensionality and dynamics characteristic of the time series. Therefore, in this study, a similarity dynamical clustering algorithm based on multidimensional shape features for time ...
WANG Ling +3 more
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FEBS Open Bio, EarlyView.Using peripheral blood for determining B‐cell or T‐cell clonality is more reliable when we use cell‐free RNA (cfRNA) because cells release blood significantly more RNA than DNA. Next‐generation sequencing (NGS) of cfRNA allows us to evaluate fragment cfRNA and evaluate clonality reliably without the need for prior determination of the specific dominant
Adam Albitar +11 more
wiley +1 more source
Comparative assessment of crystallographic and cryo‐EM models in the Protein Data Bank
FEBS Open Bio, EarlyView.Raw data obtained by X‐ray crystallography or cryo‐EM result in experimental maps, ultimately fitted by atomic models. Although the physical principles are different, the final results can be viewed, compared, and evaluated in the same way. With cryogenic electron microscopy (cryo‐EM) on track to surpass X‐ray crystallography as the preferred method ...
Alexander Wlodawer +7 more
wiley +1 more source
Subsequence Time Series Clustering
, 2009 Clustering analysis is a tool used widely in the Data Mining community and beyond (Everitt et al. 2001). In essence, the method allows us to “summarise” the information in a large data set X by creating a very much smaller set C of representative points (
Jason Chen
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Multiple Time Series Forecasting with Temporal Fusion Transformers [PDF]
, 2023 openThe goal of this thesis is to present the Temporal Fusion Transformer model and to evaluate its forecasting capabilities across multiple time series.
ZIRALDO, GAIA
core
A minimal cellulosome‐like system in Cellulosilyticum lentocellum
FEBS Open Bio, EarlyView.Cellulose‐degrading bacteria typically use cellulosomes, large multi‐enzyme complexes on a scaffold protein. In Cellulosilyticum lentocellum, we characterise a far smaller arrangement, a single scaffold bound to one cellulase through a single cohesin‐dockerin interaction.
John Allan +2 more
wiley +1 more source
Time series similarity measurement based on fractionaldifferential and its application
四川大学学报. 自然科学版, 2023 Similarity measures of time series are the basis for time series clustering, classification and other related time series analysis. The traditional distance-based similarity measure ignores the possible temporal connections of time series and treats time
YAN Wen-Peng, WANG Zhi-Tao, YUAN Xiao
doaj
Bayesian Clustering of Categorical Time Series Using Finite Mixtures of Markov Chain Models [PDF]
Two approaches for model-based clustering of categorical time series based on time- homogeneous first-order Markov chains are discussed. For Markov chain clustering the in- dividual transition probabilities are fixed to a group-specific transition matrix.
Sylvia Frühwirth-Schnatter +1 more
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