|
Showing 1 - 4 of
4 matches in All Departments
Analytical chemistry of the recent years is strongly influenced by
automation. Data acquisition from analytica instruments - and some
times also controlling of instruments - by a computer are
principally solved since many years. Availability of microcomputers
made these tasks also feasible from the economic point of view.
Besides these basic applications of computers in chemical
measurements scientists developed computer programs for solving
more sophisticated problems for which some kind of "intelligence"
is usually supposed to be necessary. Harm less numerical
experiments on this topic led to passionate discussions about the
theme "which jobs cannot be done by a computer but only by human
brain ? . If this question is useful at all it should not be ans
wered a priori. Application of computers in chemistry is a matter
of utility, sometimes it is a social problem, but it is never a
question of piety for the human brain. Automated instruments and
the necessity to work on complex pro blems enhanced the development
of automatic methods for the reduction and interpretation of large
data sets. Numerous methods from mathematics, statistics,
information theory, and computer science have been exten sively
investigated for the elucidation of chemical information; a new
discipline "chemometrics" has been established. Three different
approaches have been used for computer-assisted interpretations of
chemical data. 1. Heuristic methods try to formu late computer
programs working in a similar way as a chemist would solve the
problem. 2."
Using formal descriptions, graphical illustrations, practical
examples, and R software tools, Introduction to Multivariate
Statistical Analysis in Chemometrics presents simple yet thorough
explanations of the most important multivariate statistical methods
for analyzing chemical data. It includes discussions of various
statistical methods, such as principal component analysis,
regression analysis, classification methods, and clustering.
Written by a chemometrician and a statistician, the book reflects
the practical approach of chemometrics and the more formally
oriented one of statistics. To enable a better understanding of the
statistical methods, the authors apply them to real data examples
from chemistry. They also examine results of the different methods,
comparing traditional approaches with their robust counterparts. In
addition, the authors use the freely available R package to
implement methods, encouraging readers to go through the examples
and adapt the procedures to their own problems. Focusing on the
practicality of the methods and the validity of the results, this
book offers concise mathematical descriptions of many multivariate
methods and employs graphical schemes to visualize key concepts. It
effectively imparts a basic understanding of how to apply
statistical methods to multivariate scientific data.
1907-66: 3'791'519 1967-71: 1'314'655 (8. Sammelregister) 6'418'796
1972-76: 1'772'194 (9. Sammelregister) { online 1977 -81: 2'201'680
(10. Sammelregister) 1982-: 1'130'267 (bis Bd. 100; 30. 6. 84) Seit
1965 hat CAS 6'699'392 verschiedene chemische Verbindungen
registriert (Stand: 30. 6. 84); dazu kommen noch ca. 1,5 Mill.
Verbindungen, die vor 1965 in der Literatur erschienen sind und z.
Z. maschinell erfasst werden [6]. Wie kann man nun diese
Informationsmengen noch mit vertretbarem Auf- wand bewaltigen? Als
etwa Mitte des letzten Jahrhunderts die Zahl der Zeit- schriften so
gross wurde, dass sie vom einzelnen Wissenschaftler nicht mehr
uberschaubar war, entstanden die ersten Referatezeitschriften [1 a,
7]. Heute reicht dieses Instrument der Information in seiner
gedruckten, manuell zu be- nutzenden Form nicht mehr aus. Die
Verarbeitung und Speicherung von gro- ssen Datenmengen mit
Computern liegt auf der Hand [8]. Die heute wichtigste Einsatzform
des Computers zur gezielten (Wieder)gewinnung von Information (,
Retrieval') durch den (End)benutzer ist die, Online-Recherche'.
|
|