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The Journal of Statistical Software is a peer-reviewed open-access scientific journal that publishes papers related to statistical software.The Journal of Statistical Software was founded in 1996 by Jan de Leeuw of the Department of Statistics at the University of California, Los Angeles.
JSTOR (/ ˈ dʒ eɪ s t ɔːr / JAY-stor; short for Journal Storage) [2] is a digital library of academic journals, books, and primary sources founded in 1994. Originally containing digitized back issues of academic journals, it now encompasses books and other primary sources as well as current issues of journals in the humanities and social sciences. [3]
The book, Statistics for Spatio-Temporal Data (2011), by Cressie and Christopher K. Wikle, received two awards: the 2011 PROSE Award in the Mathematics category (for PROfessional and Scholarly Excellence, given by the Association of American Publishers), and the 2013 DeGroot Book Prize (awarded every two years by the International Society for ...
The book is aimed at a "general mathematical audience" [1] including undergraduate mathematics students with an introductory-level background in real analysis. [2] It is intended both to excite mathematicians, physicists, and computer scientists about the foundational issues in their fields, [6] and to provide an accessible introduction to the subject.
The paper covers of the course books had a different color for each of the six courses: light blue, yellow, light green (here), red, blue, dark red. The course books put out by SSMCIS were titled Unified Modern Mathematics, and labeled as Course I through Course VI, with the two volumes in each year labeled as Part I and Part II. [11]
Topics introduced in the New Math include set theory, modular arithmetic, algebraic inequalities, bases other than 10, matrices, symbolic logic, Boolean algebra, and abstract algebra. [2] All of the New Math projects emphasized some form of discovery learning. [3] Students worked in groups to invent theories about problems posed in the textbooks.
The Jensen–Shannon divergence is bounded by 1 for two probability distributions, given that one uses the base 2 logarithm: [8] (). With this normalization, it is a lower bound on the total variation distance between P and Q:
In statistics and numerical analysis, isotonic regression or monotonic regression is the technique of fitting a free-form line to a sequence of observations such that the fitted line is non-decreasing (or non-increasing) everywhere, and lies as close to the observations as possible.