A Small Celestial Atlas, Or, Maps of the Visible Heavens .. 3rd Ed., Corr. and Improved PDF Download
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Author: Moses Holden
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
Author: Moses Holden
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
Author: Geological Survey (U.S.)
Publisher:
ISBN:
Category : Map projection
Languages : en
Pages : 128
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Book Description
Author: Nathaniel Bowditch
Publisher:
ISBN:
Category : Nautical astronomy
Languages : en
Pages : 798
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Book Description
Author: Richard McElreath
Publisher: CRC Press
ISBN: 1315362619
Category : Mathematics
Languages : en
Pages : 488
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Book Description
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Author: Xiaochun Sun
Publisher: BRILL
ISBN: 9004488758
Category : History
Languages : en
Pages : 280
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Book Description
A reconstruction of the Chinese sky of two thousand years ago, based on analysis of the first star catalogue in China and other sources. Presented in six well-sized star maps for 100 BC, it is especially important for the history of astronomy. The Han sky, with five times more constellations than Ptolemy knew, reflects diverse human activities. The way in which constellations were grouped discloses a systematic cosmology, uniting universe and the state. The work of the three Han schools is comparable to Ptolemy's Almagest. With three detailed Appendices on the constellations of the three schools, well illustrated to demonstrate the relation between sky and human society, this book is valuable not only for astronomy historians and sinologists, but in general for scholars interested in the ancient cultures of Asia.
Author: M.G.J. Minnaert
Publisher: Springer Science & Business Media
ISBN: 9401034141
Category : Science
Languages : en
Pages : 259
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Book Description
Author:
Publisher:
ISBN:
Category : Industrial arts
Languages : en
Pages : 584
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Book Description
Author: Lalit Kumar
Publisher: MDPI
ISBN: 3038978841
Category : Science
Languages : en
Pages : 420
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Book Description
In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446
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Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
