TY - BOOK ID - 8581544 TI - Production and Efficiency Analysis with R PY - 2015 SN - 3319205013 3319205021 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Mathematical Statistics KW - Mathematics KW - Physical Sciences & Mathematics KW - Statistics. KW - Production management. KW - Industrial engineering. KW - Production engineering. KW - Econometrics. KW - Statistics for Business/Economics/Mathematical Finance/Insurance. KW - Operations Management. KW - Industrial and Production Engineering. KW - Operations Research/Decision Theory. KW - Operations research. KW - Statistics for Business, Management, Economics, Finance, Insurance. KW - Operational analysis KW - Operational research KW - Industrial engineering KW - Management science KW - Research KW - System theory KW - Economics, Mathematical KW - Statistics KW - Management engineering KW - Simplification in industry KW - Engineering KW - Value analysis (Cost control) KW - Manufacturing management KW - Industrial management KW - Statistical analysis KW - Statistical data KW - Statistical methods KW - Statistical science KW - Econometrics KW - Production management KW - Data processing. KW - Statistics . KW - Decision making. KW - Deciding KW - Decision (Psychology) KW - Decision analysis KW - Decision processes KW - Making decisions KW - Management KW - Management decisions KW - Choice (Psychology) KW - Problem solving KW - Manufacturing engineering KW - Process engineering KW - Mechanical engineering KW - Decision making KW - R (Computer program language). KW - GNU-S (Computer program language) KW - Domain-specific programming languages UR - https://www.unicat.be/uniCat?func=search&query=sysid:8581544 AB - This textbook introduces essential topics and techniques in production and efficiency analysis and shows how to apply these methods using the statistical software R. Numerous small simulations lead to a deeper understanding of random processes assumed in the models and of the behavior of estimation techniques. Step-by-step programming provides an understanding of advanced approaches such as stochastic frontier analysis and stochastic data envelopment analysis. The text is intended for master students interested in empirical production and efficiency analysis. Readers are assumed to have a general background in production economics and econometrics, typically taught in introductory microeconomics and econometrics courses. ER -