Statistics and Data Science

Research School on Statistics and Data Science, RSSDS 2019, Melbourne, VIC, Australia, July 24–26, 2019, Proceedings

Häftad, Engelska, 2020

689 kr

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This book constitutes the proceedings of the Research School on Statistics and Data Science, RSSDS 2019, held in Melbourne, VIC, Australia, in July 2019. The topics covered are data analysis, data science, data mining, data visualization, bioinformatics, machine learning, neural networks, statistics, and probability.

Produktinformation

Utgivningsdatum2020-01-04
Mått155 x 235 x 16 mm
Vikt423 g
FormatHäftad
SpråkEngelska
SerieCommunications in Computer and Information Science
Antal sidor263
FörlagSpringer Verlag, Singapore
ISBN9789811519598

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Operativsystem inom Data och IT
Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT

Invited Papers.- Symbolic Formulae for Linear Mixed Models.- code::proof: Prepare for most weather conditions.- Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models.- Flexible Modelling via Multivariate Skew Distributions.- Estimating occupancy and fitting models with the two-stage approach.- Component elimination strategies for mixtures of multiple scale distributions.- An introduction to approximate Bayesian computation.- Contributing Papers.- Truth, Proof, and Reproducibility: There's no counter-attack for the codeless.- On Adaptive Gauss-Hermite Quadrature for Estimation in GLMM's.- Deep learning with periodic features and applications in particle physics.- Copula Modelling of Nurses' Agitation-Sedation Rating of ICU Patients.- Predicting the whole distribution with methods for depth data analysis demonstrated on a colorectal cancer treatment study.- Resilient and Deep Network for Internet of Things (IoT) Malware Detection.- Prediction of Neurological Deterioration of Patients with Mild Traumatic Brain Injury using Machine Learning.- Spherical data handling and analysis with R package rcosmo.- On the Parameter Estimation in the Schwartz-Smith's Two-Factor Model.- Interval estimators for inequality measures using grouped data.- Exact model averaged tail area confidence intervals.

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