#StatisticalModeling

@arxivlens.bsky.social

3 months ago

CAFT: A Compositional Log-Linear Model for Microbiome Data with Zero Cells
Satten, G. A. et al.
Paper
Details
#MicrobiomeResearch #StatisticalModeling #ZeroInflation

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@freddiesteward609.bsky.social

4 months ago

Your First Multiple Linear Regression in R - A Complete Tutorial with Code Read this blog to learn how to perform your first multiple linear regression in R with clear explanations and step-by-step coding examples.

Your First Multiple Linear Regression in R - A Complete Tutorial with Code

Click here to read more:

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#MultipleLinearRegression #RProgramming #DataAnalysis #StatisticsTutorial #MachineLearning #DataScience #RStats #CodingForBeginners #ResearchMethods #StatisticalModeling

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Hacker News Companion

@hncompanion.com

5 months ago

These real-world cases highlight Bayesian analysis's value where classical methods might struggle. It's a robust tool for complex problems, offering nuanced decision-making capabilities. #StatisticalModeling 6/6

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Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

8 months ago

#TimeSeries #Forecasting #DataScience #ModelDiagnostics #ResidualAnalysis #ACF #Econometrics #StatisticalModeling #WhiteNoiseTest #DataQuality #ModelValidation

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Lifeng Kang

@lifengkang.bsky.social

9 months ago

Frontiers | Integrating Complex Systems, Statistical Modeling, Machine Learning, and AI in Cancer Research and Survival Analysis Cancer research and survival analysis present profound challenges due to the intricate, multifactorial nature of cancer development, progression, and treatme...

We edit a thematic issue:
"Integrating Complex Systems, Statistical Modeling, Machine Learning, and AI in Cancer Research and Survival Analysis." shorturl.at/WF27D
We warmly invite your contribution.
#cancer, #modelling, #ComplexSystems, #StatisticalModeling, #MachineLearning, #AI

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Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

9 months ago

Mastering Modern Time Series Forecasting : The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python 📘 Mastering Modern Time Series Forecasting (early access)This book will rise to $80+ as more chapters drop. Preorder now and lock in lifetime access.The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’s be honest — most forecasting books are either outdated, too shallow, or written by folks who’ve never actually built a real forecasting system.If you’ve ever felt frustrated by books that skip the basics, toss in code without explaining it, or barely touch on what forecasting really involves — you’re not alone.This is different.Mastering Modern Time Series Forecasting is your all-in-one, no-shortcuts guide to building reliable, high-impact forecasting systems. Whether you're just getting started or looking to deepen your expertise, this book takes you from rock-solid foundations to the latest advances in forecasting — including deep learning, transformers, and FTSM (Foundational Time Series Models).Written by a practitioner with over a decade of experience, who’s built production-grade forecasting systems for multibillion-dollar companies, this book is grounded in reality — not hype. The systems I’ve helped build have delivered multimillion-dollar business value, but I’ve also seen the other side: data science teams chasing shiny tools, only to ship systems that crash in production, fail silently, or burn through budgets without results.This book is a response to that — combining practical Python examples, real-world case studies, and a clear path to building forecasting solutions that actually work, scale, and deliver value.🔍 What You'll Learn📘 Core Forecasting FoundationsGrasp what forecast accuracy really means, master model validation strategies, and sidestep common pitfalls that trip up even experienced practitioners.📈 Classical Models, Done RightIn-depth, modern takes on ARIMA, Exponential Smoothing, and other classical statistical and econometrics models — with clarity, not complexity.🤖 Machine Learning for Time SeriesBuild feature-rich forecasts using state-of-the-art ML techniques that go far beyond black-box models.🧠 Deep Learning & TransformersExplore powerful deep learning architectures, including Transformer-based models — all with clear, readable PyTorch code.📊 FTSMs – Foundational Time Series ModelsExplore the rise of Foundational Time Series Models (FTSMs) — large, pre-trained models designed to generalize across domains, tasks, and time horizons. Think GPT for time series.🎯 Probabilistic & Interpretable ForecastingMove beyond point forecasts with uncertainty quantification, conformal prediction, SHAP, attention mechanisms, and explainability tools.📊 Real-World Case StudiesApply what you’ve learned on practical datasets across domains like retail, energy, and finance.🚀 MLOps & DeploymentLearn how to deploy, monitor, and scale your forecasting pipelines in the real world — without the headaches.👥 Who It’s For Data Scientists & ML EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom classical models to deep learning and FTSMs — no need to juggle multiple resources ever again. 📦 What You Get Instant download of the full book All code examples, datasets, and notebooks Free lifetime updates (including new chapters, errata fixes, and bonus content) Exclusive early access to upcoming bonus chapters & Q&A sessions 💸 Pricing 🎉 Introductory Price Suggested: $40 | Minimum: $35 This is the introductory price — it will increase as more chapters, tools, and content are released. If you find value or want to support the project, feel free to pay what it’s worth to you ❤️ Ready to take your forecasting skills from stats to neural nets, and from theory to real-world deployment?👉 Hit “Buy Now” and start mastering forecasting like never before.

'Mastering Modern Time Series Forecasting :' -> valeman.gumroad.com/...

#TimeSeries #Forecasting #ARIMA #ExponentialSmoothing #DataScience #Analytics #ETS #WoldsTheorem #StatisticalModeling

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Renzume.

@renzume.com

1 year ago

Latest GDPNow forecast: -2.8% GDP growth for Q1 2025, down from -1.5% on February 28
https://www.atlantafed.org/cqer/research/gdpnow
#economicforecasting #gdpanalysis #federalreserve #economicdata #statisticalmodeling

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CoListy

@colisty.netlify.app

1 year ago

Integrate R Skills into SAS for Advanced Analysis Extend R programming skills to SAS. Learn advanced modeling, data manipulation, and cross-platform integration for enhanced analytics. | CoListy

Extend R programming skills to SAS. Learn advanced modeling, data manipulation, and cross-platform integration for enhanced analytics. | CoListy
#freeonlinelearning #colisty #courselist #sasandrintegration #sas/iml #sas/stat #dataanalysis #statisticalmodeling

colisty.netlify.app/courses/sas_...

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Kontak Recruitment

@kontakrecruitment.bsky.social

1 year ago

Junior Data Analyst / Engineer (JB4991) at Kontak Recruitment in Gauteng

Junior Data Analyst / Engineer (JB4991)
Alberton, Gauteng
R15 000 to R20 000 a month CTC
Contract 6 to 12 months (May become permanent)

#SQL #Azure #PowerBI #Python #DataScience #StatisticalModeling #ETL #BusinessIntelligence

@kontakrecruitment.bsky.social
Apply: bit.ly/Dataengineer...