Suchergebnisse - (( (statene OR studiene) python code analysis ) OR ( stat python code analysis ))*

Percolation theory using Python von Malthe-Sørenssen, Anders

“… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes …”
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Statistics Using Python von Campesato, Oswald

“… This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors …”
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Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration von Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

“… : AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal …”
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Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial von Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

“… The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize …”
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LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data von Ross, Dylan H, Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M, Xu, Libin

“… Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification …”
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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data von Pakkir Shah, Abzer K., Walter, Axel, Ottosson, Filip, Russo, Francesco, Navarro-Diaz, Marcelo, Boldt, Judith, Kalinski, Jarmo-Charles J., Kontou, Eftychia Eva, Elofson, James, Polyzois, Alexandros, González-Marín, Carolina, Farrell, Shane, Aggerbeck, Marie R., Pruksatrakul, Thapanee, Chan, Nathan, Wang, Yunshu, Pöchhacker, Magdalena, Brungs, Corinna, Cámara, Beatriz, Caraballo-Rodríguez, Andrés Mauricio, Cumsille, Andres, de Oliveira, Fernanda, Dührkop, Kai, El Abiead, Yasin, Geibel, Christian, Graves, Lana G., Hansen, Martin, Heuckeroth, Steffen, Knoblauch, Simon, Kostenko, Anastasiia, Kuijpers, Mirte C. M., Mildau, Kevin, Papadopoulos Lambidis, Stilianos, Portal Gomes, Paulo Wender, Schramm, Tilman, Steuer-Lodd, Karoline, Stincone, Paolo, Tayyab, Sibgha, Vitale, Giovanni Andrea, Wagner, Berenike C., Xing, Shipei, Yazzie, Marquis T., Zuffa, Simone, de Kruijff, Martinus, Beemelmanns, Christine, Link, Hannes, Mayer, Christoph, van der Hooft, Justin J. J., Damiani, Tito, Pluskal, Tomáš, Dorrestein, Pieter, Stanstrup, Jan, Schmid, Robin, Wang, Mingxun, Aron, Allegra, Ernst, Madeleine, Petras, Daniel

“… We provide explanations and code in two scripting languages (R and Python) as well …”
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From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia von de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis …”
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Spatial Analysis Using Big Data von Hajime Seya, Yoshiki Yamagata

“… Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems …”
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An investigation on online reviews in sharing economy driven hospitality platforms: A viewpoint of trust von Cheng, Xusen, Fu, Shixuan, Sun, Jianshan, Bilgihan, Anil, Okumus, Fevzi

“… : Through content analysis and theme extraction in python, our results show the salient cognitive themes are room aesthetics, host attributes, location, repurchase intention, overall evaluation and room description …”
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Nestedness for Dummies (NeD): A user friendly web interface for exploratory nestedness analysis von Strona, Giovanni, Galli, Paolo, Seveso, Davide, Montano, Simone, Fattorini, Simone

“… Recent theoretical advances in nestedness analysis have led to the introduction of several alternative metrics to overcome most of the problems biasing the use of matrix 'temperature' calculated …”
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Statistical Analyses and Reproducible Research von Gentleman, Robert, Temple Lang, Duncan

“… It is important, if not essential, to integrate the computations and code used in data analyses, methodological descriptions, simulations, and so on with the documents that describe and rely …”
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Is Multitask Deep Learning Practical for Pharma? von Ramsundar, Bharath, Liu, Bowen, Wu, Zhenqin, Verras, Andreas, Tudor, Matthew, Sheridan, Robert P, Pande, Vijay

“… However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries …”
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Facilitating the Calculation of the Efficient Score Using Symbolic Computing von B. Sibley, Alexander, Li, Zhiguo, Jiang, Yu, Li, Yi-Ju, Chan, Cliburn, Allen, Andrew, Owzar, Kouros

“… In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself …”
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Generation of Scale-Free Assortative Networks via Newman Rewiring for Simulation of Diffusion Phenomena von Di Lucchio, Laura, Modanese, Giovanni

“… By collecting and expanding several numerical recipes developed in previous work, we implement an object-oriented Python code, based on the networkX library, for the realization of the configuration …”
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Programmieren für die Geistes- und Sozialwissenschaften von Yannick Frommherz, Simon Meier-Vieracker, Anne Josephine Matz

“… Deshalb hat das virTUos-Teilprojekt ExDiMed niedrigschwellige, modular aufgebaute Selbstlernmaterialien zur Vermittlung von Codeskills in der Programmiersprache Python entwickelt, die sich spezifisch …”
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Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models von Graham, Matthew M., Thiery, Alexandre H., Beskos, Alexandros

“… Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms, …”
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False Discovery Rate Smoothing von Tansey, Wesley, Koyejo, Oluwasanmi, Poldrack, Russell A., Scott, James G.

“… We present false discovery rate (FDR) smoothing, an empirical-Bayes method for exploiting spatial structure in large multiple-testing problems. FDR smoothing …”
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Using GNU Make to Manage the Workflow of Data Analysis Projects von Baker, Peter

“… Data analysis projects invariably involve a series of steps such as reading, cleaning, summarizing and plotting data, statistical analysis and reporting …”
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Trimmed Constrained Mixed Effects Models: Formulations and Algorithms von Zheng, Peng, Barber, Ryan, Sorensen, Reed J. D., Murray, Christopher J. L., Aravkin, Aleksandr Y.

“… Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis …”
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Missing Value Imputation in Relational Data Using Variational Inference von Fontaine, Simon, Kang, Jian, Zhu, Ji

“… In real-world networks, node attributes are often only partially observed, necessitating imputation to support analysis or enable downstream tasks …”
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