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Building Statistical Models in Python

You're reading from   Building Statistical Models in Python Develop useful models for regression, classification, time series, and survival analysis

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Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781804614280
Length 420 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Huy Hoang Nguyen Huy Hoang Nguyen
Author Profile Icon Huy Hoang Nguyen
Huy Hoang Nguyen
Paul N Adams Paul N Adams
Author Profile Icon Paul N Adams
Paul N Adams
Stuart J Miller Stuart J Miller
Author Profile Icon Stuart J Miller
Stuart J Miller
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1:Introduction to Statistics
2. Chapter 1: Sampling and Generalization FREE CHAPTER 3. Chapter 2: Distributions of Data 4. Chapter 3: Hypothesis Testing 5. Chapter 4: Parametric Tests 6. Chapter 5: Non-Parametric Tests 7. Part 2:Regression Models
8. Chapter 6: Simple Linear Regression 9. Chapter 7: Multiple Linear Regression 10. Part 3:Classification Models
11. Chapter 8: Discrete Models 12. Chapter 9: Discriminant Analysis 13. Part 4:Time Series Models
14. Chapter 10: Introduction to Time Series 15. Chapter 11: ARIMA Models 16. Chapter 12: Multivariate Time Series 17. Part 5:Survival Analysis
18. Chapter 13: Time-to-Event Variables – An Introduction 19. Chapter 14: Survival Models 20. Index 21. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

accumulated hazard function 369

Aikake Information Criterion (AIC) 278

alternative hypothesis 62

Anaconda 4

URL 4

Anderson-Darling test 91-96

ANOVA tests 117, 118

versus pairwise tests 117

ARIMA models 296-299

fitting 299-302

forecasting with 302, 303

AR(p) end-to-end example 277

building 280, 281

forecast, building 283

forecast, testing 281, 282

order of AR(p), selecting 278, 279

visual inspection 277

autocorrelation 253-257

structure 253

autocorrelation function (ACF) 165, 322

autoregressive 98

autoregressive (AR) models

AR(1) model 273-275

AR(2) model 275, 276

AR(p) end-to-end example 277

AR(p) model 272

order p, identifying using PACF 276

autoregressive integrated moving average (ARIMA) 252, 323

autoregressive...

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