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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
Model–Based Monitoring and Statistical Control
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English | 2024 | ISBN: 1032550120 | 318 Pages | PDF (True) | 10 MB
Available in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models.

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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization
Free Download Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization by Federico Moretta , Giulia Bozzano
English | PDF EPUB (True) | 2024 | 75 Pages | ISBN : 3031564596 | 7.8 MB
This book examines biomass mixture modeling and optimization.

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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
M–statistics Optimal Statistical Inference for a Small Sample
Free Download M-statistics: Optimal Statistical Inference for a Small Sample by Eugene Demidenko
English | August 22, 2023 | ISBN: 1119891795 | 240 pages | MOBI | 17 Mb
M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact optimal statistical inference for a small sample under one methodological umbrella. Two competing approaches are maximum concentration (MC) and mode (MO) statistics combined under one methodological umbrella, which is why the symbolic equation M=MC+MO. M-statistics defines an estimator as the limit point of the MC or MO exact optimal confidence interval when the confidence level approaches zero, the MC and MO estimator, respectively. Neither mean nor variance plays a role in M-statistics theory. Novel statistical methodologies in the form of double-sided unbiased and short confidence intervals and tests apply to major statistical Our new developments are accompanied by respective algorithms and R codes, available at GitHub, and as such readily available for applications. M-statistics is suitable for professionals and students alike. It is highly useful for theoretical statisticians and teachers, researchers, and data science analysts as an alternative to classical and approximate statistical inference.

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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Control (2nd Edition)
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English | 2024 | ISBN: 9819993628 | 637 Pages | PDF EPUB (True) | 70 MB
This revised book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments, and statistical quality control. It is shaped by the experience of the two teachers teaching statistical methods and concepts to engineering students. Practical examples and end-of-chapter exercises are the highlights of the text, as they are purposely selected from different fields. Statistical principles discussed in the book have a great relevance in several disciplines like economics, commerce, engineering, medicine, health care, agriculture, biochemistry, and textiles to mention a few.

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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
Information Criteria and Statistical Modeling
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English | PDF(True) | 2008 | 282 Pages | ISBN : 0387718869 | 5.4 MB
The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.

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  Author: creativelivenew1   |   25 April 2024   |   comments: 0
Building Statistical Models in Python Develop useful models for regression, classification, time series, and survival analysis
Free Download Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis by Huy Hoang Nguyen, Paul N Adams, Stuart J Miller
English | August 30, 2023 | ISBN: 1804614289 | 420 pages | PDF, EPUB | 71 Mb
Make data-driven, informed decisions and enhance your statistical expertise in Python by turning raw data into meaningful insights

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  Author: creativelivenew1   |   23 April 2024   |   comments: 0
Statistical Analysis with R Essentials For Dummies
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English | April 30th, 2024 | ISBN: 1394263422 | 192 pages | True EPUB | 1.70 MB
The easy way to get started coding and analyzing data in the R programming language

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  Author: creativelivenew1   |   23 April 2024   |   comments: 0
Computational Statistical Methodologies and Modeling for Artificial Intelligence
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English | 2023 | ISBN: 1032170808 | 515 Pages | EPUB | 43 MB
This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering.

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  Author: creativelivenew1   |   23 April 2024   |   comments: 0
A Casebook for Spatial Statistical Data Analysis A Compilation of Analyses of Different Thematic Data Sets
Free Download A Casebook for Spatial Statistical Data Analysis: A Compilation of Analyses of Different Thematic Data Sets By Daniel A. Griffith, Larry J. Layne
1999 | 524 Pages | ISBN: 0195109589 | PDF | 156 MB
This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallels between geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.

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  Author: Baturi   |   23 April 2024   |   comments: 0
Applied Statistical Modeling for Data Analysis in R
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Last updated 11/2023
Duration: 9h53m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 5.08 GB
Genre: eLearning | Language: English
Your Complete Guide to Statistical Data Analysis and Visualization For Practical Applications in R

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